65f44319c0dd62dc4d680a8ffcb8a0b632c8d890
24 Commits
| Author | SHA1 | Message | Date | |
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 Alexander Suvorov
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65f44319c0 |
Optimize computation of the endpoint cluster indices
This change improves the compression speed for both DXT and ETC encodings.
Explanation:
The vectors which are processed in the cluster indices computation step, are the very same vectors which were used in the vector quantization step. This means that every processed vector already has a specific centroid associated with it. Even though the associated centroid is not necessarily the closest one to the processed vector, the distance to the associated centroid can be used as an upper boundary of the distance to the closest centroid. This allows to efficiently perform early out while computing the distances to the other centroids.
Note: The modified algorithm is supposed to generate decompression result identical to the original version of Crunch. For this reason the centroid associated with a specific training vector is not used as an initial best solution, because it could potentially change the decompression result in cases when the processed training vector is equidistant from multiple centroids (selection of the closest centroid in such cases depends on the processing order).
DXT Testing:
The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch (revision
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Alexander Suvorov
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3053c9dd93 |
Optimize DXT endpoints computation
This change improves the compression speed for DXT encoding.
Explanation:
The main ideas used for the DXT endpoints computation optimization:
- Instead of using map in tree clusterizer, the source vectors can be stored in an array and sorted before the quantization. This might increase the amount of used memory, but is much more efficient in terms of memory reallocation.
- Endpoint caching can be used throughout the color endpoint computation, and not just within the optimize_endpoints function. The only place where endpoint caching can not be used is the final step of the try_combinatorial_encoding function, where alternate rounding is used.
- When computing endpoint codebooks, endpoint optimizer and endpoint refiner can be reused, which eliminates unnecessary memory reallocations.
DXT Testing:
The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch (revision
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Alexander Suvorov
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3e12aff909 |
Fix miscellaneous compiler warnings
DXT Testing:
The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch (revision
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Alexander Suvorov
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bec4114bea |
Add compression support for ETC2A textures
This change makes it possible to use Crunch algorithms for ETC textures with Alpha channel.
Explanation:
For simplicity, Crunch algorithms currently do not use ETC2 specific modes (T, H or P). For this reason, the currently used ETC2A compression format is technically equivalent to ETC1 + Alpha. Note that ETC2 encoding is a superset of ETC1, so any texture, which consists of ETC1 color blocks and ETC2 Alpha blocks, can be correctly decoded by an ETC2A (ETC2_RGBA8) decoder.
Compression scheme for ETC2 Alpha blocks is equivalent to the compression scheme for DXT5 Alpha blocks. ETC2 Alpha endpoint clusterization is performed based on the very same output of the Alpha palettizer which is used for DXT5 Alpha. The only part which is actually different is the Alpha endpoint optimization step.
In order to perform ETC2 Alpha encoding, we can first run the already existing algorithm for DXT5 Alpha endpoint optimization, in order to obtain the initial approximate solution. Then the approximate solution is refined based on the ETC2 Alpha modifier table. When performing raw ETC2A encoding, all the 16 ETC2 Alpha modifiers are used during optimization. However, when performing ETC2A quantization, for performance reasons, only 2 Alpha modifiers are currently used (modifier 13, which allows to perform precise approximation on short Alpha intervals, and modifier 11, which has more or less regularly distributed values, and is used for large Alpha intervals).
For compatibility reasons, ETC2 color compression wrappers have also been added to the code, though, as has been mentioned before, at the current moment ETC2 specific modes are not used, so ETC2 color compression is currently equivalent to ETC1 compression.
The ETC decoder functionality has been significantly extended, Crunch is now capable to decode ETC2 and ETC2A textures (input ETC2 textures can have T, H or P blocks).
In order to use ETC2A compression, use the -ETC2A command line option (i.e. "crunch_x64.exe -ETC2A input.png"). By default, compressed ETC2A textures will be decompressed into KTX file format.
DXT Testing:
The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch (revision
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Alexander Suvorov
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e972e0b480 |
Improve selector weight computation for ETC1 encoding
This change improves compression ratio for ETC1 encoding.
Explanation:
When computing endpoint weights for ETC1 encoding, it is possible to use delta luma instead of the Euclidean distance between the outer endpoint colors, as it gives approximately the same result.
When computing selector weight, it is important to take into account the following factors:
- The bigger is the difference between the outer endpoint colors, the bigger error can be introduced by the corresponding selector, therefore the bigger should be the weight of that selector. In the original Crunch algorithm, the selector weight is proportional to the squared distance between the outer endpoint colors. Such optimization improves PSNR, but it might also introduce significant distortion in smooth areas of the image. In order to mitigate this effect, it is proposed to limit the maximum difference between the endpoint colors (currently delta luma is limited by 100).
- Blocks with low difference between the outer endpoint colors introduce relatively small error, so their selectors should have smaller weights. In the original algorithm it is achieved by using squared distance between the outer endpoint colors, though the effect can be amplified further by using powers higher than 2 (currently it is set to 2.7), which improves PSNR.
In the original Crunch algorithm the encoding weights are initialized non-symmetrically (and are set to math::lerp(1.15f, 1.0f, 1.0f / 7.0f) for horizontal split and to math::lerp(1.15f, 1.0f, 2.0f / 7.0f) for vertical split). It is proposed to use the same encoding weight for both splits in case of ETC1 (the used coefficient 0.972 has been computed as math::lerp(1.15f, 1.0f, 1.5f / 7.0f) / 1.15f).
The ETC1 quantization parameters have been adjusted accordingly to preserve the average Luma PSNR.
DXT Testing:
The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch (revision
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Alexander Suvorov
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a0044903aa |
Use diagonal endpoint references for ETC1 encoding
This change slightly improves compression ratio for ETC1 encoding, and also demonstrates how to adjust the endpoint reference configuration for a specific texture format.
Note: This modification alters the output file format for ETC1 encoding and makes it incompatible with the previous revisions.
Explanation:
In addition to the standard endpoint references (to the top and to the left ETC1 blocks), it is also possible to use an endpoint reference to the top-left diagonal neighbour ETC1 block. Specifically, the first ETC1 subblock will now have the reference value of 3 if the endpoint is copied from the second subblock of the top-left neighbour ETC1 block.
DXT Testing:
The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch (revision
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Alexander Suvorov
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7402f3d4f3 |
Use endpoint references for all the ETC1 subblocks
This change significantly improves compression ratio for ETC1 encoding.
Note: This modification alters the output file format for ETC1 encoding and makes it incompatible with the previous revisions.
Explanation:
Previously, for simplicity, endpoint references for ETC1 encoding have been only computed withing the tiling area. Now endpoint references are computed for all the ETC1 subblocks. This means that endpoints can now be inherited from the surrounding ETC1 blocks, which significantly improves the compression ratio.
Endpoint references for ETC1 subblocks are encoded in the following way:
- The first ETC1 subblock has the reference value of 0 if the endpoint is decoded from the input stream, the value of 1 if the endpoint is copied from the second subblock of the left neighbour ETC1 block, and the value of 2 if the endpoint is copied from the first subblock of the top neighbour ETC1 block.
- The second ETC1 subblock has the reference value of 0 if the endpoint is copied from the first subblock, the value of 1 if the endpoint is decoded from the input stream and the corresponding ETC1 block is split horizontally, and the value of 2 if the endpoint is decoded from the input stream and the corresponding ETC1 block is split vertically.
DXT Testing:
The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch (revision
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Alexander Suvorov
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205f8a171d |
Use 4x4 selector dictionary for ETC1 compression
This change significantly improves the ETC1 compression ratio. Explanation: As has been shown in the previous commit, each element of the ETC1 endpoint dictionary should correspond to a single ETC1 base color. In order to achieve near-lossless compression with unlimited dictionary, it has been proposed to use 4x2 or 2x4 ETC1 subblocks as building elements, defined by a single endpoint and selector. This scheme is equivalent to the original DXT compression scheme, expect the different size of the block, defined by the dictionary elements. Now let's pay attention to the following interesting observation. Even though in the original DXT compression scheme the dictionaries are defined in such a way, so that both endpoints and selectors from the dictionaries correspond to the same size of the decoded block (in case of DXT it is 4x4), there is no requirement for this implied by the Crunch algorithms. In fact, selector dictionary and indices are defined after the endpoint optimization is complete. At this point each image pixel is already associated with a specific endpoint. At the same time, the selector computation step is only using those per-pixel endpoint associations as an input information, so the size and the shape of the blocks, defined by selector dictionary elements, does not depend in any way on the size or shape of the blocks, defined by endpoint dictionary elements. In other words, the endpoint space of the texture can be split into one set of blocks, defined by endpoint dictionary and endpoint indices. And the selector space of the texture can be split into absolutely different set of blocks, defined by selector dictionary and selector indices. Endpoint blocks can be different in size from the selector blocks, as well as endpoint blocks can overlap in arbitrary way with the selector blocks, and such setup will still be fully compatible with the existing Crunch algorithms. In the current commit, the size of the block, defined by an ETC1 selector dictionary element, has been set to 4x4, which significantly improves the compression ratio (the ETC1 quantization parameters have been adjusted to preserve the average Luma PSNR). Future research: The discovered property of the Crunch algorithms opens another dimension for optimization of the compression ratio. Specifically, the quality of the compressed selectors can now be adjusted in two ways: by changing the size of the selector dictionary and by changing the size of the selector block. Note that both DXT and ETC formats have selectors encoded as plain bits in the output format, so there is no technical limitation on the size or shape of the selector block (though, for performance reasons, non-power-of-two selector blocks might require some specific optimizations in the decoder). DXT Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps using DXT1 encoding] Original: 1582222 bytes / 28.859 sec Modified: 1482780 bytes / 13.326 sec Improvement: 6.28% (compression ratio) / 53.82% (compression time) [Compressing Kodak set with mipmaps using DXT1 encoding] Original: 2065243 bytes / 36.996 sec Modified: 1931586 bytes / 18.121 sec Improvement: 6.47% (compression ratio) / 51.02% (compression time) ETC Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). The ETC1 quantization parameters have been selected in such a way, so that ETC1 compression gives approximately the same average Luma PSNR as the corresponding DXT1 compression (which is equal to 34.044 dB for the Kodak test set compressed without mipmaps using DXT1 encoding and default quality settings). [Compressing Kodak set without mipmaps using ETC1 encoding] Total size: 1692204 bytes Total time: 17.528 sec Average bitrate: 1.434 bpp Average Luma PSNR: 34.057 dB |
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Alexander Suvorov
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f284523b15 |
Add compression support for ETC1 textures
Explanation: Crunch algorithms are normally used for compression of DXTn textures. However, Crunch algorithms are much more powerful, and with some minor adjustments, those algorithms can be directly used to compress other texture formats. For example, the current commit demonstrates how to use the existing Crunch algorithms to compress ETC1 textures. Basics: In general, Crunch is performing the following steps: - tiling (determines block encodings) - quantization of the tile endpoints (determines endpoint indices) - optimization of the endpoints for each tile group (determines endpoint dictionary) - quantization of the selectors (determines selector indices) - selector refinement for each selector group (determines selector dictionary) - compression of the previously determined block encodings, dictionaries and indices Dictionary element: When applying Crunch algorithms to a new texture format, it is necessary to first define the dictionary element. In context of Crunch, this means thats the whole image consists of smaller non-overlapping blocks, while the contents of each individual block is determined by an endpoint and a selector from the corresponding dictionaries. For example, in case of DXT format, each endpoint and selector codebook element corresponds to a 4x4 pixel block. In general, the size of the blocks, which form the encoded image, depends on the texture format and quality considerations. It is proposed to define the dictionaries according to the following limitations: - The dictionary elements should be compatible with the existing Crunch algorithms, while the image blocks defined by those dictionary elements should be compatible with the texture encoding format. - It should be possible to cover a wide range of image quality and bitrates by just changing the size of the endpoint and selector dictionaries. If there is no limitation on the dictionary size, the encoding should preferably become lossless or near-lossless (not considering the quality loss implied by the texture format itself). In case of ETC1, the texture format itself determines the minimal size of the image block, defined by endpoint and selector: it can be either 2x4 or 4x2 rectangle, aligned to the borders of the 4x4 grid. It is not possible to use higher granularity, because each of those rectangles can have only one base color, according to the ETC1 format. For the same reason, any image block, defined by an endpoint and a selector from the dictionary, should be combined from those aligned 2x4 or 4x2 rectangles. Let's investigate the possibilities for the endpoint dictionary. According to the ETC1 format, each 4x4 ETC1 block is split in half, while each ETC1 subblock has it's own base color and a modifier table index. In fact, the base color and the modifier table index simply define the high and the low colors for the subblock (while there are some limitations on the position of those high and low colors, implied by the ETC1 encoding). If we define the endpoint dictionary element in such a way that it contains information about more than one ETC1 base color, then such a dictionary will become incompatible with the existing tile quantization algorithm, and the reason for this is the following. The Crunch tiling algorithm first performs quantization of all the tile pixel colors, down to just 2 colors. Then it quantizes all those color pairs, coming from different tiles. This approach works quite well for 4x4 DXT blocks, as those 2 colors approximately represent the principle component of the tile pixel colors. In case of ETC1 however, mixing together pixels, which correspond to different base colors, does not make much sense, as each group of those pixels has it's own low and high color values, independent from other groups. When those pixels are mixed together, the information about the original principle components of each subblock gets lost. For the mentioned reason, each endpoint dictionary element should correspond to a single ETC1 base color. In such case, the tile quantization algorithm will work almost the same way as for DXT format. Each pair of colors, generated by the tile palletizer, will normally have the subblock base color value somewhere in the middle between those 2 colors, so quantizing those color pairs should also automatically quantize the corresponding base colors. Moreover, each color pair implicitly contains information about the modifier table index (which corresponds to the distance between the high and the low colors), and therefore the corresponding table index will also get automatically quantized. Endpoint and selector dictionary elements, which define a single 2x4 or 4x2 ETC1 subblock, are fully compatible with the existing Crunch algorithms (because each ETC1 subblock is associated with a single base color and a single modifier table index). At the same time, those subblocks are minimal possible blocks, which can be defined by a dictionary element for ETC1 format (as has been shown earlier). Of course, it is also possible to use blocks larger than 2x4 or 4x2 (assuming that all the ETC1 subblocks, which form such a block, will have the same base color and the same modifier table index), however, with a larger block area it would be not possible to achieve near-lossless quality when the dictionary size is not limited. As the result, it is proposed to define the dictionaries in the following way: - Each element of the endpoint dictionary defines a single base color and a single modifier table index of a 2x4 or a 4x2 pixel block (which represents an ETC1 subblock). - Each endpoint is encoded as 3555 (3 bits for the table index and 5 bits for each component of the base color). - Each element of the selector dictionary defines selectors for a 2x4 or a 4x2 block. - Each selector is encoded using 16 bits. ETC1-specific adjustments: In case of DXT, the size of the encoded block is 4x4, while the tiling is performed in a 8x8 area (4 blocks). In case of ETC1, the tiling can be performed either in a 4x4 area (2 blocks), or in a 8x8 area (8 blocks), while other possibilities are either not symmetrical or too complex. For simplicity it is proposed to use 4x4 area for tiling. There are therefore 3 possible encodings: the 4x4 block is not split (encoded with a single endpoint), the 4x4 block is split horizontally, the 4x4 block is split vertically. For simplicity, endpoint references are currently determined only within the tiling area, while the encoding of the endpoint references has been adjusted in the following way: - The first ETC1 subblock will always have the reference value of 0 - The second ETC1 subblock can have the reference value of 0 if it has the same endpoint as the first subblock (note that in such case the flip of the ETC1 block does not need to be defined), the value of 1 if the corresponding ETC1 block is split horizontally, and the value of 2 if the corresponding ETC1 block is split vertically According to the ETC1 format, the base colors within an ETC1 block can be encoded either as 444 and 444, or differentially as 555 and 333. For simplicity, this aspect is currently not taken into account (all the endpoints are encoded as 3555 in the codebook). If it appears that the base colors in the resulting ETC1 block can not be encoded differentially, the decoder will convert both base colors from 555 to 444. At first, it might look like the ETC1 block flipping can bring some complications for Crunch, as the subblock structure might not look like a grid. This can be easily resolved by mirroring all the vertical ETC1 blocks across the main diagonal of the block after the tiling step (so that all the ETC1 subblocks will become 4x2 and form a regular grid). The decoder can mirror the ETC1 selector back according to the decoded block flip. The code adjustments for the ETC1 compression support are pretty straightforward and mostly trivial. Just note that when format-specific adjustments affect performance critical code, it makes sense to duplicate the body of the affected function and perform format-specific optimizations in each copy of the function individually. For performance reasons, the following 4 functions now got both ETC and DTX specific versions: - determine_tiles_task_etc() is an ETC-optimized version of the determine_tiles_task(), where dxt_fast class has been replaced with the etc1_optimizer class. - determine_color_endpoint_codebook_task_etc() is an ETC-optimized version of the determine_color_endpoint_codebook_task(), where dxt1_endpoint_optimizer class has been replaced with the etc1_optimizer class. - pack_color_endpoints_etc() is an ETC-optimized version of the pack_color_endpoints(), where 565565 DXT color endpoint encoding has been replaced with 3555 ETC color endpoint encoding. - unpack_etc1() is an ETC version of the unpack_dxt1() function. The color_quality_power_mul and m_adaptive_tile_color_psnr_derating parameters for ETC1 format have been selected in such a way, so that ETC1 compression gives approximately the same average Luma PSNR as the equivalent DXT1 compression, when compressing the Kodak test set without mipmaps using default quality. In order to use ETC1 compression, use the -ETC1 command line option (i.e. "crunch_x64.exe -ETC1 input.png"). By default, compressed ETC1 textures will be decompressed into KTX file format. DXT Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps using DXT1 encoding] Original: 1582222 bytes / 28.876 sec Modified: 1482780 bytes / 13.255 sec Improvement: 6.28% (compression ratio) / 54.10% (compression time) [Compressing Kodak set with mipmaps using DXT1 encoding] Original: 2065243 bytes / 36.987 sec Modified: 1931586 bytes / 18.068 sec Improvement: 6.47% (compression ratio) / 51.15% (compression time) ETC Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). The ETC1 quantization parameters have been selected in such a way, so that ETC1 compression gives approximately the same average Luma PSNR as the corresponding DXT1 compression (which is equal to 34.044 dB for the Kodak test set compressed without mipmaps using DXT1 encoding and default quality settings). [Compressing Kodak set without mipmaps using ETC1 encoding] Total size: 1887265 bytes Total time: 14.954 sec Average bitrate: 1.600 bpp Average Luma PSNR: 34.049 dB |
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Alexander Suvorov
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39b85b74c2 |
Optimize selector codebook creation algorithm
This change significantly improves compression speed. Explanation: When generating selector codebook, pixel selectors can be processed in groups, while the intermediate error results for those groups can be precalculated. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.865 sec Modified: 1482780 bytes / 13.340 sec Improvement: 6.28% (compression ratio) / 53.78% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.988 sec Modified: 1931586 bytes / 18.087 sec Improvement: 6.47% (compression ratio) / 51.10% (compression time) |
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Alexander Suvorov
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5822475b22 |
Completely remove all the chunk related code from the encoder and decoder
This change slightly improves compression speed and simplifies further modification of the code. Explanation: Additional performance boost is achieved by using linear representation for selectors and storing block selectors in a single uint32/uint64. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.927 sec Modified: 1494501 bytes / 17.301 sec Improvement: 5.54% (compression ratio) / 40.19% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.992 sec Modified: 1945365 bytes / 22.548 sec Improvement: 5.80% (compression ratio) / 39.05% (compression time) |
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Alexander Suvorov
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e7d458aa22 |
Switch from chunk encoding to block encoding while performing image quantization
This change improves compression speed and simplifies further modification of the code. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.947 sec Modified: 1494501 bytes / 17.642 sec Improvement: 5.54% (compression ratio) / 39.05% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.965 sec Modified: 1945365 bytes / 22.989 sec Improvement: 5.80% (compression ratio) / 37.81% (compression time) |
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Alexander Suvorov
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cd9ba9b615 |
Switch from chunk encoding to block encoding after the tile computation
This change improves compression speed and simplifies further modification of the code. Explanation: This change is required for further optimization of the tile computation code. Additional performance boost is achieved by moving the tile palettizing into the tile computation thread. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.928 sec Modified: 1494501 bytes / 18.259 sec Improvement: 5.54% (compression ratio) / 36.88% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.978 sec Modified: 1945365 bytes / 23.857 sec Improvement: 5.80% (compression ratio) / 35.48% (compression time) |
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Alexander Suvorov
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7b6f456399 |
Optimize selector quantization, assignment and refinement
This change significantly improves compression speed. Explanation: The main ideas used for selector computations optimization: - possible pixel values for each endpoint can be cached - the distances between the possible pixel values and the actual pixels values within a block can be cached for fast error computation during selector assignment - selector refinement can be efficiently integrated with the selector assignment, as it is based on the same set of cached error values - using block encoding instead of chunk encoding for both endpoints and selectors eliminates extra levels of indirection Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.953 sec Modified: 1494501 bytes / 19.667 sec Improvement: 5.54% (compression ratio) / 32.07% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.998 sec Modified: 1945365 bytes / 25.642 sec Improvement: 5.80% (compression ratio) / 30.69% (compression time) |
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Alexander Suvorov
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b8349dfac8 |
Use block encoding to store intermediate selectors after endpoint quantization
This change simplifies further modification of the code. Explanation: This change is required for further optimization of the quantization code. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.935 sec Modified: 1494501 bytes / 24.528 sec Improvement: 5.54% (compression ratio) / 15.23% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.982 sec Modified: 1945365 bytes / 32.308 sec Improvement: 5.80% (compression ratio) / 12.64% (compression time) |
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Alexander Suvorov
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1ef829ed6f |
Move alpha endpoint refinement into the alpha endpoint optimization thread
This change improves compression speed when using alpha channel. Explanation: As the alpha endpoint refinement does not depend on the alpha selector codebook computation, it can be safely moved into the alpha endpoint optimization thread. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.912 sec Modified: 1494501 bytes / 24.128 sec Improvement: 5.54% (compression ratio) / 16.55% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.985 sec Modified: 1945365 bytes / 31.741 sec Improvement: 5.80% (compression ratio) / 14.18% (compression time) |
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Alexander Suvorov
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9c289fc621 |
Move color endpoint refinement into the color endpoint optimization thread
This change significantly improves compression speed. Explanation: If we take a closer look at the color endpoint refinement, we can see that the input for the color refinement comes directly from the color endpoint optimization step, while the selector codebook computation does not affect the color endpoint refinement at all. Therefore color endpoint refinement can be safely moved into the endpoint optimization thread. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.899 sec Modified: 1494501 bytes / 24.043 sec Improvement: 5.54% (compression ratio) / 16.80% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.884 sec Modified: 1945365 bytes / 31.586 sec Improvement: 5.80% (compression ratio) / 14.36% (compression time) |
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Alexander Suvorov
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d0b6f5759b |
Switch from chunk encoding to block encoding after quantization
This change simplifies further modification of the code. Explanation: Considering that chunks are no longer used in the output format, it makes sense to also remove chunk related code from the intermediate processing. This modification also allows to use endpoint references from the leftmost block to the rightmost block in the previous scanline (wrapped reference to the left). Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.846 sec Modified: 1494501 bytes / 25.628 sec Improvement: 5.54% (compression ratio) / 11.16% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.869 sec Modified: 1945365 bytes / 33.497 sec Improvement: 5.80% (compression ratio) / 9.15% (compression time) |
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Alexander Suvorov
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5258727545 |
Remove duplicate endpoints and selectors from the codebooks
This change significantly improves the compression ratio. Explanation: By default, the size of the endpoint and selector codebooks is calculated based on the number of blocks in the image and the quality parameter, while the actual complexity of the image does not affect the initial codebook size. So the target codebook size is selected in such a way, that even complex images can be approximated well enough. At the same time, normally, the lower is the complexity of the image, the higher is the density of the quantized vectors. Considering that vector quantization is performed using floating point computations, and the quantized endpoints have integer components, high density of quantized vectors will result in large number of duplicate endpoints. As the result, some identical endpoints are being represented by multiple different indices, which significantly affects the compression ratio. Note that this is not the case for selectors, as their corresponding vector components are rounded after quantization, but instead it leads to some duplicate selectors in the codebook being not used. In the modified version of the algorithm all the duplicate codebook entries are merged together, unused entries are removed from the codebooks, the endpoint and selector indices are updated accordingly. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.835 sec Modified: 1494630 bytes / 25.637 sec Improvement: 5.54% (compression ratio) / 11.09% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.875 sec Modified: 1946533 bytes / 33.546 sec Improvement: 5.75% (compression ratio) / 9.03% (compression time) |
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Alexander Suvorov
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13b1faa48d |
Reorder chunks in each scanline in the left-to-right manner
This change slightly improves compression ratio and compression time. Explanation: The efficiency of the Crunch encoding scheme depends on the similarity between the neighbour chunks. For this reason in original version of Crunch the order of chunks is reversed after each scanline, so that there is no jump from one side of the image to another at the image borders. The problem here is that inside of each chunk, the blocks are normally ordered in a usual up-to-down-left-to-right manner, regardless of the chunk scanning order. While on the forward scan we normally need to perform diagonal jumps (+1, +1) in order to get to the next chunk, on the reverse scan we normally need to perform much larger (-3, +1) jumps, which usually defeats the advantage of not having discontinuity at the image borders. Note: This modification alters the output format and makes it incompatible with the previous revisions. Testing: The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch. [Compressing Kodak set without mipmaps] Original: 1582222 bytes / 28.882 sec Modified: 1579618 bytes / 28.743 sec Improvement: 0.16% (compression ratio) / 0.48% (compression time) [Compressing Kodak set with mipmaps] Original: 2065243 bytes / 36.920 sec Modified: 2061499 bytes / 36.833 sec Improvement: 0.18% (compression ratio) / 0.24% (compression time) |
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Alexander Suvorov
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7c02055d05 | Reformat the source files. The source files have been reformatted using: clang-format.exe -style="{BasedOnStyle: Google, AllowAllParametersOfDeclarationOnNextLine: false, AllowShortFunctionsOnASingleLine: Inline, AllowShortIfStatementsOnASingleLine: false, AllowShortLoopsOnASingleLine: false, ColumnLimit: 0, DerivePointerAlignment: false, SortIncludes: false}" | ||
 richgel99@gmail.com
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f71b49be60 | Initial checkin of v1.04 - KTX file format support, basic ETC1 compression/decompression, Linux makefile with proper gcc options, lots of high-level improvements to get crnlib into a state where I can more easily add additional formats. | ||
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richgel99@gmail.com
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f63e26aee6 | v1.03 prerelease - Full Linux port of crnlib/crunch, in progress - still more testing to do, and some cmd line options (such as -timestamp) don't work under linux yet, but the core stuff (compression/decompression/transcoding) should work fine and performance under Linux is comparable to Windows. The 3 examples haven't been ported yet. | ||
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richgel99@gmail.com
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9f98ea7e22 |