The cortex transform: rapid computation of simulated neural images
Computer Vision, Graphics, and Image Processing
Wavelets and subband coding
JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
The Colour Image Processing Handbook (Optoelectronics, Imaging and Sensing)
The Colour Image Processing Handbook (Optoelectronics, Imaging and Sensing)
Wavelets and Human Visual Perception in Image Compression
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
A New Wavelet Based Compression Scheme Replicating Human Visual System Processing
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 03
Visibility of wavelet quantization noise
IEEE Transactions on Image Processing
Locally adaptive perceptual image coding
IEEE Transactions on Image Processing
Wavelet-based color image compression: exploiting the contrast sensitivity function
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Dynamic contrast-based quantization for lossy wavelet image compression
IEEE Transactions on Image Processing
An information fidelity criterion for image quality assessment using natural scene statistics
IEEE Transactions on Image Processing
VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images
IEEE Transactions on Image Processing
Wavelet filter evaluation for image compression
IEEE Transactions on Image Processing
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In this paper a Human Visual System based adaptive quantization scheme is proposed. The proposed algorithm supports perceptually lossless as well as lossy compression. The algorithm uses a transform based compression approach using the wavelet transform, and has incorporated vision models for the compression of both luminance and chrominance components. The major strength of the coder is the incorporation of the vision model for the chrominance components and the optimum way in which the scales are distributed among the luminance and chrominance components to achieve higher compression ratios. The perceptual model developed for the color components gives flexibility for giving more compression for the color components without causing any color degradations. For each image the visual thresholds are evaluated and an optimum bit allocation is done in such a way that the quantization error is always less than the visual distortion for the given rate. To validate the strength of the proposed algorithm, the perceptual quality of the images reconstructed using the proposed coder is compared with the images reconstructed with JPEG2000 standard coder, for the same compression. To evaluate the perceptual quality of the compressed images latest perceptual quality matrices such as Structural Similarity Index, Visual Information Fidelity and Visual Signal-to-Noise Ratio are used. The results obtained reveal that the proposed structure gives excellent improvement in perceptual quality compared to the existing schemes, for both lossy as well as lossless compression. These advantages make the proposed algorithm a good candidate for replacing the quantizer stage of the current image compression standards.