Presented are two new methods based on entropy for reconstructing images compressed with the Discrete Cosine transform. One method is based upon a sequential implementation of the Minimum Relative Entropy Principle; the other is based upon the Maximum Entropy Principle. These will be compared with each other and with the conventional method employing the Inverse Discrete Cosine transform. Chapter 2 describes the traditional use of the Discrete Cosine transform for image compression. Chapter 3 explains the theory and implementation of the entropy-based reconstructions. It introduces a fast algorithm for the Maximum Entropy Principle. Chapter 4 compares the numerical performance of the three reconstruction methods. Chapter 5 shows the theoretical convergence limit of the iterative implementation of the Minimum Relative Entropy Principle to equal the limit of the convergence of the Maximum Relative Entropy method. Preliminary results of this thesis were presented at Southeastern '87 in Tampa. Final results will be presented at the Annual Meeting of the American Optical Society in Rochester on October 19, 1987.
Tzannes, Nicolaos S.
Master of Science (M.S.)
College of Engineering
Length of Campus-only Access
Masters Thesis (Open Access)
Bodenschatz, John S., "Image Reconstruction After Transform Coding Using Relative Entropy and Maximum Entropy" (1987). Retrospective Theses and Dissertations. 5095.
Contributor (Linked data)
University of Central Florida. College of Engineering [VIAF]