计算机应用研究2011，Vol.28Issue(8)：3171-3173,3177,4.DOI:10.3969/j.issn.1001-3695.2011.08.103
基于学习字典的图像类推方法
Image analogies method based on learned dictionary
摘要
Abstract
To improve the computational efficiency of image analogies, this paper presented a novel image analogies method based on learned dictionary. The method first segmented sample image pairs to patches, which were unified for sparse coding and training learned dictionary. Then built the sparse association between the patch pairs,and defined as a priori knowledge for image analogies. The method mainly included two processes; training learned dictionary and image analogies. The dictionary training process could be off-line achieved to improve the computation speed,accordingly realized numerous samples training. During image analogies process, this method used the linear optimization problem of sparse prior instead of searching and matching in general methods,and improved the computational efficiency remarkably. Experiments with texture-by-numbers,stylized filter,etc. Show the high efficiency of our method.关键词
图像类推/稀疏表示/学习字典/l1范数Key words
image analogies/ sparse representation/ learned dictionary/ 2,-norm分类
计算机与自动化引用本文复制引用
李民,程建,汤万琼..基于学习字典的图像类推方法[J].计算机应用研究,2011,28(8):3171-3173,3177,4.基金项目
中国博士后基金资助项目(20080441198) （20080441198）
电子科技大学青年科技基金重点资助项目(JX0804) （JX0804）
