Set Redundancy, the Enhanced Compression Model, and Methods for Compressing Sets of Similar Images

ACKNOWLEDGMENTS I am deeply indebted to my advisor Dr. John Tyler for his continuous support and encouragement throughout my graduate studies. His patience, enthusiasm, and generous contribution of time and resources have greatly helped me to achieve my goals. He has been more than my advisor, as he often made me feel part of his family. I am especially thankful for his trust in my ideas and abilities and for the opportunities he has offered me. I would like to thank all the members of my graduate committee and particularly Dr. for all the knowledge and support they offered me during my graduate studies at LSU. I wish to thank and express my appreciation to my parents. They have given me direction in life, never letting me take the easy way, and they have offered me one of the most precious gifts: the values that have shaped my character. I am particularly grateful to Maria for her immeasurable emotional and intellectual support throughout our graduate school years. She has played a major role in my decision to pursue a Ph.D. after my Master's degree. She has read all my manuscripts and provided thoughtful and constructive comments and criticisms, even though Computer Science is not her field. She has always been there to share my ideas, dreams, frustrations, and excitements. They have given me the opportunity and the resources to test my theory and obtain the experimental results that are presented in this dissertation. Figure 13: Translating the origin to the " maximum point " of the cluster, or " maximum image " .. ABSTRACT Image compression is the process of reducing the number of bits required to represent an image. This can be achieved by reducing (or ideally, eliminating) various types of redundancy that exist in the imaging data. All current image compression methods are based on the same theoretical model, which targets redundancy found in individual images. However, this model ignores an additional type of redundancy that exists in sets of similar images, the " set redundancy ". The source of set redundancy is the common information existing in more than one image in a set of similar images. Set redundancy can be recognized by the appearance of similar pixel values at the same image regions, comparable image histograms, similar image features, or analogous distributions of edges. This research explores the concept of set redundancy and establishes its importance …