Embedded Image Coding Using ZeroBlocks of Subband/Wavelet Coefficients and Context Modeling
DCC '01 Proceedings of the Data Compression Conference
A very low bit rate algorithm based on hierarchical subband scanning
ACS'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 7
An efficient rearrangement of wavelet packet coefficients for embedded quad-tree image coding
MUSP'07 Proceedings of the 7th WSEAS International Conference on Multimedia Systems & Signal Processing
Highly scalable hybrid image coding scheme
Digital Signal Processing
Set Partition Coding: Part I of Set Partition Coding and Image Wavelet Coding Systems
Foundations and Trends in Signal Processing
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
A Hybrid Image Coder Based on SPIHT Algorithm with Embedded Block Coding
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Adaptive Selection and Rearrangement of Wavelet Packets for Quad-Tree Image Coding
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Context-based rate distortion estimation and its application to wavelet image coding
WSEAS Transactions on Information Science and Applications
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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In this paper we propose a simple image compression method that efficiently codes transform images. This work has been stimulated by the EZW and SPIHT image compression methods. However, the compression method we describe is not embedded in the sense employed previously, nor does it utilise the concept of a zerotree or related structure. The only characteristic of transform imagery utilised is that of energy clustering in frequency and in space. Two variants of the coding method are considered for image compression. One gives a hierarchical image code when employed with a discrete wavelet transform, while the other is suitable for block based coding.