1 research outputs found
Reversible Denoising and Lifting Based Color Component Transformation for Lossless Image Compression
An undesirable side effect of reversible color space transformation, which
consists of lifting steps (LSs), is that while removing correlation it
contaminates transformed components with noise from other components. Noise
affects particularly adversely the compression ratios of lossless compression
algorithms. To remove correlation without increasing noise, a reversible
denoising and lifting step (RDLS) was proposed that integrates denoising
filters into LS. Applying RDLS to color space transformation results in a new
image component transformation that is perfectly reversible despite involving
the inherently irreversible denoising; the first application of such a
transformation is presented in this paper. For the JPEG-LS, JPEG 2000, and JPEG
XR standard algorithms in lossless mode, the application of RDLS to the RDgDb
color space transformation with simple denoising filters is especially
effective for images in the native optical resolution of acquisition devices.
It results in improving compression ratios of all those images in cases when
unmodified color space transformation either improves or worsens ratios
compared with the untransformed image. The average improvement is 5.0-6.0\% for
two out of the three sets of such images, whereas average ratios of images from
standard test-sets are improved by up to 2.2\%. For the efficient
image-adaptive determination of filters for RDLS, a couple of fast
entropy-based estimators of compression effects that may be used independently
of the actual compression algorithm are investigated and an immediate filter
selection method based on the detector precision characteristic model driven by
image acquisition parameters is introduced.Comment: Keywords: Reversible color space transformation; Lifting technique;
Denoising; Reversible denoising and lifting step; Detector precision
characteristic; Lossless image compressio