武汉工程大学学报2017，Vol.39Issue(3)：267-272,6.DOI:10.3969/j.issn.1674⁃2869.2017.03.011
稀疏表示中字典学习的影响因子研究
Influence Factors of Dictionary Learning in Sparse Representation
摘要
Abstract
We studied the key factors influencing the construction quality of dictionary matrix in sparse representation,and represented them quantitatively. The factors such as the number of images,patch size, dictionary columns and patch step were adjusted as parameters and the dictionary matrix was generated. Combined with the coefficient matrix,the original image was reconstructed,and the dictionary quality was evaluated by using the image quality assessment indices of peak signal to noise ratio and structural similarity index metric. Experiments on CMU_PIE_Face database demonstrate that the resulting dictionary has the best ability to represent the original image at image numbers of 500,patch size of 4 px,dictionary columns of 512 and patch step of 2 px. We found that the quantitative representation of key factors in sparse representation can accelerate the dictionary learning process,simplify the complexity of the model,improve the quality of the dictionary abstraction layer,and show stronger image expression.关键词
稀疏表示/字典学习/字典精度/图像质量评价指标Key words
sparse representation/dictionary learning/dictionary accuracy/image quality assessment index分类
信息技术与安全科学引用本文复制引用
赵娜,赵彤洲,邹冲,刘莹,蔡敦波..稀疏表示中字典学习的影响因子研究[J].武汉工程大学学报,2017,39(3):267-272,6.基金项目
国家自然科学基金(61103136) （61103136）
武汉工程大学创新基金(CX2015057) （CX2015057）
武汉工程大学创新基金(CX2016070) （CX2016070）
