5.8

Recovery Methods for Postprocessing of Compressed Images

Y. Yang,     Illinois Institute of Technology

N.P. Galatsanos,     University of Ioannina

A.K. Katsaggelos,     Northwestern University

1 Introduction

2 Basic Theory of Projections onto Convex Sets

3 Projections onto Convex Sets-Based Image Recovery from Compressed Data

3.1 Overview of the Methodology

3.2 The JPEG Discrete Cosine Transform Algorithm

3.3 Vector Notation

3.4 Constraint Set Based on Transform Coefficients

3.5 Constraints Based on Prior Knowledge

3.6 Recovery Algorithm

3.7 Adaptive Processing

3.8 Choice of Weight Factors in W for Adaptive Processing

3.9 Determination of Constant λ in the Projector Pwc

3.10 The Recovery Algorithm

4 Maximum A Posteriori Estimation ...

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