桂林电子科技大学学报2017，Vol.37Issue(3)：187-191,5.
基于自适应字典学习的乘性噪声去除模型
Multiplicative noise removal model based on adaptive dictionary
摘要
Abstract
In order to remove the noise of image,a new image multiplicative noise removal model based on sparse representation and adaptive dictionary is proposed.PCA dictionary and iteration shrinkage algorithm are used to update the sparse code.Newton-iteration method is used to obtain the restored image of log-domain.By an exponential function and error correction,the denoising image is obtained in the real domain.Experimental results demonstrate that compared with several existing noise suppression algorithms,this model can hold important information of the image better while effectively removing multiplicative noise.关键词
字典学习/稀疏表示/乘性噪声/非局部Key words
dictionary learning/sparse representation/multiplicative noise/nonlocal分类
信息技术与安全科学引用本文复制引用
何成凤,王学文,陈利霞..基于自适应字典学习的乘性噪声去除模型[J].桂林电子科技大学学报,2017,37(3):187-191,5.基金项目
国家自然科学基金(61362021,61272216,61572147) （61362021,61272216,61572147）
广西自然科学基金(2013GXNSFDA019030,2014GXNSFDA118035) （2013GXNSFDA019030,2014GXNSFDA118035）
广西高校图像图形智能处理重点实验室基金(GIIP201408,GIIP201503,GIIP201501,GIIP201401) （GIIP201408,GIIP201503,GIIP201501,GIIP201401）
广西高校中青年教师基础能力提升计划(KY2016YB162) （KY2016YB162）
