The Effect of Image Rotation on UTV Decomposition

摘要：

Since the singular value decomposition (SVD) consumes high computational complexity on updating its eigenvectors and eigenvalues when new data are included, an alternate rank-revealing orthogonal decomposition that can eliminate this problem such as the UTV decomposition is one of our particular interest. This paper presents a study on directions of principal structures of the images and their effects when the UTV decomposition is employed. The relationship between the UTV decomposition and SVD is also explored. The proposed image denoising algorithm illustrates that the UTV decomposition can efficiently decompose images with vertical/horizontal structures into only a few component as well as the SVD.

作者: Yodchanan Wongsawat

作者单位: Department of Biomedical Engineering, Mahidol University, 25/25 Phuttamonthon Sai4 Rd., Salaya, Nakhonpathom 73170, Thailand

会议类型: 国际会议

会议名称: 2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)

会议地点: 镇江

会议语种:英文

页码: 1467-1470

在线出版日期: 2008-07-07（万方平台首次上网日期，不代表论文的发表时间）