A patch-based structural masking model with an application to compression
Journal on Image and Video Processing - Special issue on patches in vision
An HVS based adaptive quantization scheme for the compression of color images
Digital Signal Processing
Visually lossless JPEG2000 using adaptive visibility thresholds and visual masking effects
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
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This paper presents a contrast-based quantization strategy for use in lossy wavelet image compression that attempts to preserve visual quality at any bit rate. Based on the results of recent psychophysical experiments using near-threshold and suprathreshold wavelet subband quantization distortions presented against natural-image backgrounds, subbands are quantized such that the distortions in the reconstructed image exhibit root-mean-squared contrasts selected based on image, subband, and display characteristics and on a measure of total visual distortion so as to preserve the visual system's ability to integrate edge structure across scale space. Within a single, unified framework, the proposed contrast-based strategy yields images which are competitive in visual quality with results from current visually lossless approaches at high bit rates and which demonstrate improved visual quality over current visually lossy approaches at low bit rates. This strategy operates in the context of both nonembedded and embedded quantization, the latter of which yields a highly scalable codestream which attempts to maintain visual quality at all bit rates; a specific application of the proposed algorithm to JPEG-2000 is presented.