文献类型：期刊文献

英文题名：General form for obtaining discrete orthogonal moments

作者：Zhu, H.[1];Liu, M.[2];Shu, H.[3];Zhang, H.[3];Luo, L.[3]

机构：[1]E China Univ Sci & Technol, Dept Elect & Commun Engn, Shanghai 200237, Peoples R China;[2]Univ Salford, Ctr Networking & Telecommun Res, Sch Comp Sci & Engn, Salford M5 4WT, Lancs, England;[3]Southeast Univ, Sch Comp Sci & Engn, Lab Image Sci & Technol, Nanjing 210096, Peoples R China

年份：2010

卷号：4

期号：5

起止页码：335

外文期刊名：IET IMAGE PROCESSING

收录：;EI(收录号：20104013277394);WOS:【SCI-EXPANDED(收录号:WOS:000282911900001)】；

基金：The authors would like to thank the anonymous referees for their helpful comments and suggestions. This work has been supported by National Natural Science Foundation of China under grant 60975004, National Basic Research Program of China under grant 2010CB732503 and the Natural Science Foundation of Jiangsu Province under grant BK2008279.

语种：英文

外文关键词：Image compression - Group theory - Image representation

摘要：Discrete orthogonal moments such as Tchebichef moments and Krawtchouk moments are more powerful in image representation than traditional continuous orthogonal moments. However, less work has been done for the summarisation of these discrete orthogonal moments. This study proposes two general forms which will simplify and group the discrete orthogonal Tchebichef and Krawtchouk polynomials and their corresponding moments, and discusses their importance in theories and applications. Besides, the proposed general form can be used to obtain other three discrete orthogonal moments: Hahn moments, Charlier moments and Meixner moments. Computations of these discrete orthogonal polynomials are also discussed in this task, including the recurrence relation with respect to variable x and order n. Some properties of these discrete orthogonal moments, which are of particular value to image processing applications, such as energy compact capability and signal decorrelation, are also presented. Finally, the study evaluates these discrete orthogonal moments in terms of the capacity of image reconstruction and image compression, and discusses the importance of the proposed general form in theories and engineering.