Spatial intra prediction has been added recently to the latest video coding standard H.264/AVC. In the intra
prediction of H.264/AVC, there are 9, 9 and 4 prediction modes for 4×4, 8×8 and 16×16 blocks, respectively.
Prediction signals are generated by using one or several reference pixels. The value of a reference pixel is copied
as the prediction value. In some prediction modes, we calculate a weighted mean by averaging several pixels.
The same prediction value is copied to several of the pixels lying in the prediction direction. However, if original
image has patterns like gradations, the residual energy could increase which would result in low coding efficiency.
In this paper, we propose a new intra prediction that generates prediction signals with a spatial gradient to deal
with this problem. Simulation results show that it improves the picture quality and reduce the bit-rate by about
0.14 dB and 1.0 % on average for CIF sequences, respectively. It is also confirmed that our method is effective
at high bit-rates.
KEYWORDS: Image compression, Quantization, Image quality, Visualization, Digital imaging, Data conversion, Matrices, Color difference, Data compression, Image analysis
In image coding, the distribution of quantization error is uniform
across the transformed domain (i.e., coding error). To minimize
visually perceptible noise, the quantization step size should suit the
most sensitive area in the color space used. Consequently, we can
expect to improve the coding efficiency while achieving the same
subjective quality by adopting a perceptually uniform color space.
Currently used image coding schemes such as JPEG and MPEG, make
extensive use of the YCbCr color space. However, its perceptual
non-uniformity is significant. In this paper, we introduce the
uniform color space 'LST', which is obtained by smoothly deforming
the CIE xy chromaticity diagram with a look-up table with 333 morphing
points so that every MacAdam JND (just noticeable difference) ellipse
is mapped onto or close to a unit circle. Test color images that use
this LST color space, as well as the CIELAB, CIELUV and YCbCr spaces,
are JPEG coded. The coding algorithm itself does not need to be
changed. Subjective comparisons by six subjects of the decoded images
to the originals show the superiority of LST to the three other
spaces; the most commonly-used YCbCr was ranked last despite its
highest PSNR. No significant difference was observed between CIELUV
and CIELAB.
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