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This paper proposes a unified coding algorithm for lossless and near-lossless color image compression that exploits the correlations between RGB signals. For lossless coding, a reversible color transform is proposed that removes the correlations between RGB signals while avoiding any finite word length limitation. Next, the lossless algorithm is extended to a unified coding algorithm of lossless and near-lossless compression that can control the distortion level in the magnitude on the RGB plane. Experimental results show the effectiveness of the proposed algorithm.

The JBIG2 standard supports lossless and lossy coding models for text, halftone, and generic regions in bi-level images. For the JBIG2 lossy halftone compression mode, halftones are descreened before encoding. Previous JBIG2 descreening implementations produce high-quality images for clustered dot halftones at high compression rates but significantly degrade the image quality for stochastic halftones, even at much lower rates. In this paper, we develop (1) a flexible, computationally efficient, JBIG2-compliant method for compressing stochastic halftones that reduces noise, artifacts, and blurring; (2) quality measures for linear and nonlinear distortion in compressed halftones; and (3) rate-distortion tradeoffs for the encoder parameters.

LOGO-I (LOw COmplexity LOssless COmpression for Images) is the algorithm at the core of the new ISO/ITU standard for lossless and near-lossless compression of continuous-tone images, JPEG-LS. The algorithm was conceived as a "low complexity projection" of the universal context modeling paradigm, matching its modeling unit to a simple coding unit based on Golomb codes. The JPEG-LS standard evolved after successive refinements of the core algorithm, and a description of its design principles and main algorithmic components is presented in this paper. LOCO-I/JPEG-LS attains compression ratios similar or superior to those obtained with state-of-the-art schemes based on arithmetic coding. Moreover, it is within a few percentage points of the best available compression ratios, at a much lower complexity level.

The emerging JBIG2 standard allows compliant encoders to achieve very high compression rates on bi-level images, especially when images are properly segmented into regions of line-art, halftones and text. We propose a fast method that is very effective at separating text from non-text regions, even when the regions are nonrectangular or have skew. Our method can also detect regions of reverse-coloured text. In most cases, our method increases the compression performance of the encoder. More importantly, our method can improve encoding speeds considerably, often by an order of magnitude.

A method for compression of large binary images is proposed for applications where spatial access to the image is required. The proposed method is a two-stage combination of forward-adaptive modeling and backward-adaptive context based compression with re-initialization. Compression stage is performed by JBIG arithmetic coder, namely the QM-coder. The method improves the compression performance significantly in comparison to JBIG if it is used in a similar manner. Only minor modifications to the existing software implementations are required. Implementation details are provided.