HEVC (Ver. 1) adopts two lossless modes:
- IPCM – actually ‘copy-paste’ mode (even not DPCM)
- Lossless Entropy
Lossless Entropy Mode
This mode is signaled by PPS parameter transquant_bypass_enabled_flag .
Lossless entropy mode is applied on CU-level, i.e. some CUs can be coded as lossless while the rest is coded in regular lossy manner. In some scenarion it might be useful to encode a region (e.g. Logo) in lossless entropy mode. If a CU is coded as entropy lossless this CUs is indeed identical copy of the original one since in-loop filters (Deblocking,SAO) are not applied on the pixels of the CU (notice in-loop filters can modify pixels).
Technically the lossless entropy mode is performed by skipping transform and quantization phases, only residuals are entropy coded.
It might seem the entropy lossless mode is less time consuming than regular lossy mode (because no transform, no quantization/de-quantization, no deblocking, no SAO). However, the lossless entropy mode produces much more bins and as a result CABAC tends to work much harder. It would not a surprise that lossless entropy mode would take more cycles than lossy one.
i conducted several tests with x265 and found that lossless entropy mode is about twice slower than regular lossy mode.
Remarks:
- To enable the lossless entropy mode in x265 it’s necessary to type
'--lossless'in the command line. - Another possibility is to use ffmpeg and to set ‘-crf 0’ :
ffmpeg -s 1920x1080 -i test.yuv -c:v libx265 -crf 0 -y output.h265 - In lossless mode the bitrate is redundant since an encoder has no tool to control bitrate.
- According to Fatih Kamisli (see the paper “LOSSLESS COMPRESSION IN HEVC WITH INTEGER-TO-INTEGER TRANSFORMS”, 2016), HEVC Range Extensions (Ver. 2) provides RDPCM and other tools that improve the lossless compression coding efficiency by 5-10% and also reduce the encoding/decoding time or complexity by ~%10.
- According to HEVC spec., only QP=4 makes quantization truly lossless.
Philosophical Note:
In lossless compression you always should bear in mind the principle of pigeonholes. According to the principle of pigeonholes there is no universal tool which squeezes all NxN pictures. If you succeed with a tool to squeeze a subset of NxN pictures, then there necessarily exist pictures which your tool extends instead of compressing.
Note: lossless coding is sometimes called entropy coding.
23+ years’ programming and theoretical experience in the computer science fields such as video compression, media streaming and artificial intelligence (co-author of several papers and patents).
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