Title :
Image Decomposition and Texture Segmentation via Sparse Representation
Author :
Zhang, Fan ; Ye, Xiaoqiong ; Liu, Wenyu
Author_Institution :
Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan
fDate :
6/30/1905 12:00:00 AM
Abstract :
Decomposing an image into a texture part and a non-texture (cartoon) part, as well as grouping the texture part into several homogeneous subparts, is studied in this letter. The so-called texture part is composed of both the self-similar structure and the oscillatory noise. The self-similar structure of each homogenous subtexture is captured in its principal subspace. Both the segmentation and the decomposition are essentially related to sparse representation and are united to a framework.
Keywords :
image representation; image segmentation; image texture; principal component analysis; homogenous subtexture; image decomposition; oscillatory noise; self-similar structure; sparse representation; texture segmentation; Convolution; Frequency; Hilbert space; Image decomposition; Image segmentation; Kernel; Minimization methods; Principal component analysis; Unsupervised learning; Watermarking; Clustering; principal component analysis (PCA); sparse representation; texture; total variation; unsupervised learning;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2008.2002722