MULTIRESOLUTION-INFORMATION ANALYSIS FOR IMAGES

被引：12
作者：
ROMANROLDAN, R
QUESADAMOLINA, JJ
MARTINEZAROZA, J
机构：
[1] Departamento de Física Aplicada, Facultad de Ciencias, Universidad de Granada
[2] Departamento de Matemática Aplicada, Facultad de Ciencias, Universidad de Granada
来源：
SIGNAL PROCESSING | 1991年 / 24卷 / 01期
关键词：
IMAGE ANALYSIS; MULTIRESOLUTION; ENTROPY PER PIXEL; GIBBS DISTRIBUTION; MAXIMUM ENTROPY PRINCIPLE; MAJORIZATION;
D O I：
10.1016/0165-1684(91)90085-W
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper is devoted to the analysis and characterization of images in the framework of multiresolution. We use the gray level histogram entropy as the best representation of the information provided by an image. First, we introduce the concept of 'entropy per pixel' provided by a class of images given at a certain resolution level, and then we study the 'entropy per pixel versus resolution' diagrams for particular images and classes of images. Maximum entropy principle, theory of majorization and other results from information theory are used to prove several properties of these diagrams. The most important property asserts that the entropy per pixel is strictly decreasing with respect to the resolution, i.e., a coarser resolution observation results in a loss of information. Some examples illustrate the results obtained. Several open problems and applications are proposed.
引用
收藏
页码：77 / 91
页数：15
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