The old implementation in enc/near_lossless.c performing a separate
preprocessing step is used only when a prediction filter is not used,
otherwise a new implementation integrated into lossless_enc.c is used.
It retains the same logic for converting near lossless quality into max
number of bits dropped, and for adjusting the number of bits based on
the smoothness of the image at a given pixel. As before, borders are not
changed.
Then, instead of quantizing raw component values, the residual after
subtract green and after prediction is quantized according to the
resulting number of bits, taking care to not cross the boundary between
255 and 0 after decoding. Ties are resolved by moving closer to the
prediction instead of by bankers’ rounding.
This results in about 15% size decrease for the same quality.
Change-Id: If3e9c388158c2e3e75ef88876703f40b932f671f
- The result is now indeed closest among possible results for all inputs, which
was not the case for bits>4, where the mapping was not even monotonic because
GetValAndDistance was correct only if the significant part of initial fit in
a byte at most twice.
- The set of results for a larger number of bits dropped is a subset of values
for a smaller number of bits dropped. This implies that subsequent
discretizations for a smaller number of bits dropped do not change already
discretized pixels, which improves the quality (changes do not accumulate)
and compression density (values tend to repeat more often).
- Errors are more fairly distributed between upwards and downwards thanks to
bankers’ rounding, which avoids images getting darker or lighter in overall.
- Deltas between discretized values are more repetitive. This improves
compression density if delta encoding is used.
Also, the implementation is much shorter now.
Change-Id: I0a98e7d5255e91a7b9c193a156cf5405d9701f16
Updated the near-lossless level mapping and make it correlated to lossy
quality i.e 100 => minimum loss (in-fact no-loss) and the visual-quality loss
increases with decrease in near-lossless level (quality) till value 0.
The new mapping implies following (PSNR) loss-metric:
-near_lossless 100: No-loss (bit-stream same as -lossless).
-near_lossless 80: Very very high PSNR (around 54dB).
-near_lossless 60: Very high PSNR (around 48dB).
-near_lossless 40: High PSNR (around 42dB).
-near_lossless 20: Moderate PSNR (around 36dB).
-near_lossless 0: Low PSNR (around 30dB).
Change-Id: I930de4b18950faf2868c97d42e9e49ba0b642960
Enable the WebP near-lossless feature by pre-processing the image to smoothen
the pixels.
On a 1000 PNG image corpus, for which WebP lossless (default settings) gets
25% compression gains, following is the performance of near-lossless feature
at various '-near_lossless' levels:
-near_lossless 90: 30% (very very high PSNR 54-60dB)
-near_lossless 75: 38% (very high PSNR 48-54dB)
-near_lossless 50: 45% (high PSNR 42-48dB)
-near_lossless 25: 48% (moderate PSNR 36-42dB)
-near_lossless 10: 50% (PSNR 30-36dB)
WebP near-lossless is specifically useful for discrete-tone images like
line-art, icons etc.
Change-Id: I7d12a2c9362ccd076d09710ea05c85fa64664c38
Cleaup Near-lossless code
- Simplified and refactored the code.
- Removed the requirement (TODO) to allocate the buffer of size WxH and work
with buffer of size 3xW.
- Disabled the Near-lossless prr-processing for small icon images (W < 64 and H < 64).
Change-Id: Id7ee90c90622368d5528de4dd14fd5ead593bb1b
Compared to previous mode it gives another 10-30% improvement in compression keeping comparable PSNR on corresponding quality settings.
Still protected by the WEBP_EXPERIMENTAL_FEATURES flag.
Change-Id: I4821815b9a508f4f38c98821acaddb74c73c60ac
This compresses the uimage using lossless compression and controlable
decimating pre-process.
Code is under WEBP_EXPERIMENTAL_FEATURE while it's being experimented with.
Change-Id: I8b7f4cfcc3c6afc52a556102842bdbb045ed5ee8
