Optimized atom position and coefficient coding for matching pursuit-based image compression

Authors:
Alireza Shoa;Shahram Shirani
Affiliations:
Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada;Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
Venue:
IEEE Transactions on Image Processing
Year:
2009

Citing 11
Cited 1

Introduction to data compression (2nd ed.)

Introduction to data compression (2nd ed.)
JPEG 2000: Image Compression Fundamentals, Standards and Practice

JPEG 2000: Image Compression Fundamentals, Standards and Practice
Atomic Decomposition by Basis Pursuit

SIAM Review
Tree-Based Pursuit: Algorithm and Properties

IEEE Transactions on Signal Processing
A posteriori quantization of progressive matching pursuit streams

IEEE Transactions on Signal Processing
Quantization

IEEE Transactions on Information Theory
In-loop atom modulus quantization for matching pursuit and its application to video coding

IEEE Transactions on Image Processing
Low-rate and flexible image coding with redundant representations

IEEE Transactions on Image Processing
Adaptive Rate-Distortion Optimal In-Loop Quantization for Matching Pursuit

IEEE Transactions on Image Processing
Very low bit-rate video coding based on matching pursuits

IEEE Transactions on Circuits and Systems for Video Technology
Modulus quantization for matching-pursuit video coding

IEEE Transactions on Circuits and Systems for Video Technology

Joint optimization coding for level and map information in H.264/AVC

Image Communication

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Abstract

In this paper, we propose a new encoding algorithm for matching pursuit image coding. We show that coding performance is improved when correlations between atom positions and atom coefficients are both used in encoding. We find the optimum tradeoff between efficient atom position coding and efficient atom coefficient coding and optimize the encoder parameters. Our proposed algorithm outperforms the existing coding algorithms designed for matching pursuit image coding. Additionally, we show that our algorithm results in better rate distortion performance than JPEG 2000 at low bit rates.