A structure-adaptive matching pursuit subspace search algorithm for effective image sparse representation

作者：Sun Yu Bao^*; Xiao Liang; Wei Zhi Hui; Liu Qing Shan

来源：Chinese Journal of Computers, 2012, 35(8): 1751-1758.

DOI：10.3724/SP.J.1016.2012.01751

• Adaptive matching pursuits
• Fast numerical algorithm
• Geometrical structure
• Hot research topics
• Matching pursuit
• Multi-component dictionaries
• Multicomponents
• Quad trees
• Quad-tree decomposition
• Search Algorithms
• Single components
• Sparse decomposition
• Sparse representation
• Structure type
• Texture structure

It is hot research topics that how to design a proper image sparse representation model and a fast numerical algorithm for effective sparse decomposition of images. At first structure adaptive multi-component sparse representation model of image is constructed. This model adaptively segments an image into quad-tree block in terms of geometrical structure character and relative threshold, and each homogenous block is classified as one of plain, edge or texture structure. At the same time, a multi-component dictionary is construed to represent each block. Furthermore, a structure adaptive matching pursuit subspace search algorithm is proposed to obtain effective image sparse representation. When seeking for sparse decomposition of every quad-tree block, it is only to search in subspace of single component sub-dictionary with the same structure type as current block. Due to the reduction of dimension of image and complexity of searching in the dictionary, our algorithm for sparse representation is effective and fast. The experimental results confirm the efficiency of our algorithm.

• 出版日期2012
• 单位南京大学