Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Context-Based Entropy Coding Lossy Wavelet Image Compression
DCC '97 Proceedings of the Conference on Data Compression
Context Quantization with Fisher Discriminant for Adaptive Embedded Wavelet Image Coding
DCC '99 Proceedings of the Conference on Data Compression
CREW: Compression with Reversible Embedded Wavelets
DCC '95 Proceedings of the Conference on Data Compression
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Space-frequency quantization for wavelet image coding
IEEE Transactions on Image Processing
An embedded still image coder with rate-distortion optimization
IEEE Transactions on Image Processing
Progressive image coding using trellis coded 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
On-Line Adaptation in Image Coding with a 2-D Tarp Filter
DCC '02 Proceedings of the Data Compression Conference
Embedded Image Coding Using ZeroBlocks of Subband/Wavelet Coefficients and Context Modeling
DCC '01 Proceedings of the Data Compression Conference
Generic Adoption of Spatial Steganalysis to Transformed Domain
Information Hiding
E-LTW: an enhanced LTW encoder with sign coding and precise rate control
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
On the use of genetic algorithms to improve wavelet sign coding performance
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
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Both a magnitude and a sign define wavelet transform coefficients. While promising algorithms exist for efficiently coding the transform coefficient magnitudes, current wavelet image coding algorithms are not efficient at coding the sign of the transform coefficients. It is generally assumed that there is no compression gain to be obtained from entropy coding of the sign. Only recently have some authors begun to investigate this component of wavelet image coding.In this paper, sign coding is examined in detail in the context of an embedded wavelet image coder. It is shown that PSNR improvements up to .7 dB are possible from an efficient modeling and entropy coding of the coefficients signs, combined with a new extrapolation technique, which is used to improve the final estimate of insignificant coefficients. These sign coding techniques are applicable to any genre (e.g. zero-tree, context-model) of embedded wavelet image coder.