A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
Wavelets and subband coding
Synthesis of VLSI Architectures for Two-Dimensional Discrete Wavelet Transforms
ASAP '95 Proceedings of the IEEE International Conference on Application Specific Array Processors
Image compression by texture modeling in the wavelet domain
IEEE Transactions on Image Processing
Hierarchical partition priority wavelet image compression
IEEE Transactions on Image Processing
A jointly optimized subband coder
IEEE Transactions on Image Processing
Space-frequency quantization for wavelet image coding
IEEE Transactions on Image Processing
Visibility of wavelet quantization noise
IEEE Transactions on Image Processing
A new method of robust image compression based on the embedded zerotree wavelet algorithm
IEEE Transactions on Image Processing
A wavelet-based analysis of fractal image compression
IEEE Transactions on Image Processing
Wavelet transform and scale space filtering of fractal images
IEEE Transactions on Image Processing
Image coding using wavelet transforms and entropy-constrained trellis-coded quantization
IEEE Transactions on Image Processing
Wavelet filter evaluation for image compression
IEEE Transactions on Image Processing
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
Integrated Computer-Aided Engineering
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A perceptually-lossless wavelet-based image compression algorithm and architecture working directly in the R-G-B color domain is proposed. Even though the highest compression ratios are achievable in the Luminance-Chrominance domain, image sensors generate data commonly in a subsampled R-G-B format. Many real-time applications (e.g., a low cost digital camera) prohibit the on-line conversion of data from R-G-B format to any other format. Therefore, in these applications, it is desirable to apply the compression directly on R-G-B data. Our compression scheme is based on derived perceptually-lossless quantizing thresholds, and can be mapped into an ASIC yielding very high throughput. Examples illustrating the performance of the coder are presented.