计算机工程与科学2018，Vol.40Issue(1)：72-78,7.DOI:10.3969/j.issn.1007-130X.2018.01.011
基于局部字典搜索和多原子匹配追踪的图像逼近算法
Image approximation based on local dictionary searching and multi-atom matching pursuit
摘要
Abstract
Global searching in dictionary with single atom being selected in each iteration leads to greedy algorithms' high complexity in sparse decomposition.Given this,we propose an improved matching pursuit (MP) algorithm named local dictionary searching and multi-atoms matching pursuit (LMMP).Calculation showed that the order of kernel atoms in the adjacent generation of MP algorithm is basically stable,the best atom just to search in local dictionary consisting of the front order atoms.Searching for multiple incoherent atoms on single iteration to further improve the speed of MP algorithm.Reduce the approximation error by updating the residual image one by one atom in turn.Theoretical analysis indicates that the LMMP algorithm is convergent and its time complexity is several orders of magnitude lower than the MP.Experimental results show that the LMMP algorithm outperforms other global searching methods in computational speed and approximation performance.关键词
匹配追踪/局部搜索/快速哈特莱变换/多原子Key words
matching pursuit/local search/fast Hartley transform/multi-atom分类
信息技术与安全科学引用本文复制引用
黄亚飞,梁昔明,樊绍胜..基于局部字典搜索和多原子匹配追踪的图像逼近算法[J].计算机工程与科学,2018,40(1):72-78,7.基金项目
国家自然科学基金(61473049) （61473049）
中央支持地方项目(PXM2013_014210_000173) （PXM2013_014210_000173）
