Lossless image compression scheme with binary layers scanning

Abstract

In this work a novel lossless coding approach for color images is considered. It is based on local-adaptive combination of inter-and intra-component prediction. New context modeling method based on decomposition to binary layers is used for prediction errors. Compression performance of proposed algorithm is proved by experimental results obtained for popular public benchmarks.

Performance Analysis of Prediction Methods for Lossless Image Compression

“…One of the key features of BLS is adaptation to correlation of prediction errors, so-called residual correlation. As demonstrated in [3] this algorithm of prediction errors encoding outperforms conventional lossless image compression standards, e.g. JPEG-LS [4,5] and JPEG-2000 [6].…”

“…To estimate compression performance all prediction errors are encoded using JPEG-LS part 2 [5], JPEG-2000 [6] and BLS [3] codecs. For color images JPEG-LS part 2 codec uses reversible color transform which is similar to transform described in JPEG-2000 (lossless compression mode).…”

“…BLS codec is used in combination with various intra-and inter-component predictors analyzed in this paper [3]. MED or ALCM are used as intra-component predictors for the first (green) image component processing.…”

“…One of the additional goals of this paper is performance improvement of lossless image compression scheme with Binary Layers Scanning (BLS) introduced in previous work [3]. One of the key features of BLS is adaptation to correlation of prediction errors, so-called residual correlation.…”

A lossless coding scheme for maps using binary wavelet transform

“…A gray scale image undergoes bit plane coding and the bi-level layers are extracted starting from most significant bit to least significant bit or vice versa to exploit the advantage of sparsity after the Binary Wavelet Transformation (BWT). In Gilmutdinov et al (2014), the lossless coding is done on images by performing binary layer decomposition, which follows predictive coding to achieve compression.…”