JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
Multidimensional signal compression using multiscale recurrent patterns
Signal Processing - Image and Video Coding beyond Standards
Least-square prediction for backward adaptive video coding
EURASIP Journal on Applied Signal Processing
Edge-directed prediction for lossless compression of natural images
IEEE Transactions on Image Processing
On Dictionary Adaptation for Recurrent Pattern Image Coding
IEEE Transactions on Image Processing
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The Multidimensional Multiscale Parser-based (MMP) image coding algorithm, when combined with flexible partitioning and predictive coding techniques (MMP-FP), provides state-of-the-art performance. In this paper we investigate the use of adaptive least-squares prediction in MMP. The linear prediction coefficients implicitly embed the local texture characteristics, and are computed based on a block's causal neighborhood (composed of already reconstructed data). Thus, the intra prediction mode is adaptively adjusted according to the local context and no extra overhead is needed for signaling the coefficients. We add this new context-adaptive linear prediction mode to the other MMP prediction modes, that are based on the ones used in H.264/AVC; the best mode is chosen through rate-distortion optimization. Simulation results show that least-squares prediction is able to significantly increase MMP-FPs rate-distortion performance for smooth images, leading to better results than the ones of state-of-theart, transform-based methods. Yet with the addition of least-squares prediction MMP-FP presents no performance loss when used for encoding non-smooth images, such as text and graphics.