Theses and Dissertations - UTB/UTPA
Date of Award
Master of Science (MS)
Dr. Ping-Sing Tsai
Dr. Zhixiang Chen
Dr. Peter A. Ng
Traditional histogram or statistics based 2D image similarity/dissimilarity metrics fail to handle conjugate pair of black and white images, due to the lack of spatial information in the measurement. Recently proposed Compression-based Dissimilarity Measure (CDM)  based on the concept of Kolmogorov complexity has provided a different paradise for similarity measurement. However, without a clear definition how to “concatenate” two 2D images, CDM has difficulties to directly apply with 2D images. In this thesis, an entropy -based 2D image dissimilarity measure is proposed within the same Kolmogorov complexity paradise. The spatial relationship between images is embedded in our metric, and the actual compression of images is not needed once the entropy values are obtained. The proposed metric has been tested for scene change detection application, and encouraging results are presented here.
University of Texas-Pan American
Copyright 2005 Meng-Hung Wu. All Rights Reserved.