JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
Vector Quantization with Zerotree Significance Map for Wavelet Image Coding
ASILOMAR '95 Proceedings of the 29th Asilomar Conference on Signals, Systems and Computers (2-Volume Set)
Tree-structured vector quantization with significance map for wavelet image coding
DCC '95 Proceedings of the Conference on Data Compression
JPEG2000 Standard for Image Compression: Concepts, Algorithms and VLSI Architectures
JPEG2000 Standard for Image Compression: Concepts, Algorithms and VLSI Architectures
SBHP-a low complexity wavelet coder
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
SPIHT image compression without lists
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
Generalizing SPIHT: a family of efficient image compression algorithms
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
Three-dimensional SPIHT coding of volume images with random access and resolution scalability
Journal on Image and Video Processing - Regular
A successive approximation vector quantizer for wavelet transform image coding
IEEE Transactions on Image Processing
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
Successive refinement lattice vector quantization
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
Motion differential set partition coding for image sequence and video compression
Journal of Visual Communication and Image Representation
Distributed video coding with progressive significance map
Journal of Visual Communication and Image Representation
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This monograph describes current-day wavelet transform imagecoding systems. As in the first part, steps of the algorithms areexplained thoroughly and set apart. An image coding system consistsof several stages: transformation, quantization, set partition oradaptive entropy coding or both, decoding including rate control,inverse transformation, de-quantization, and optional processing(see Figure 1.6). Wavelet transform systems can provide manydesirable properties besides high efficiency, such as scalabilityin quality, scalability in resolution, and region-of-interestaccess to the coded bitstream. These properties are built into theJPEG2000 standard, so its coding will be fully described. SinceJPEG2000 codes subblocks of subbands, other methods, such as SBHP(Subband Block Hierarchical Partitioning) [3] and EZBC (EmbeddedZero Block Coder) [8], that code subbands or its subblocksindependently are also described. The emphasis in this part is theuse of the basic algorithms presented in the previous part in waysthat achieve these desirable bitstream properties. In this vein, wedescribe a modification of the tree-based coding in SPIHT (SetPartitioning In Hierarchical Trees) [15], whose output bitstreamcan be decoded partially corresponding to a designated region ofinterest and is simultaneously quality and resolution scalable.This monograph is extracted and adapted from the forthcomingtextbook entitled Digital Signal Compression: Principles andPractice by William A. Pearlman and Amir Said, CambridgeUniversity Press, 2009.