Image Block Compression Based on Dual-Learning Dictionaries

被引:0
作者
Pan Wenchao [1 ]
Li Bo [2 ]
Chong Yanwen [3 ]
机构
[1] Wuhan Univ Sci & Technol, Int Sch, Wuhan, Peoples R China
[2] Wuhan Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan, Peoples R China
[3] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Peoples R China
来源
2020 12TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI) | 2020年
基金
中国国家自然科学基金;
关键词
dual-learning dictionaries; blocking compression; compression model; image reconstruction; sparse representation; SPARSE ANALYSIS MODEL; K-SVD; DESIGN;
D O I
10.1109/icaci49185.2020.9177627
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To improve the nonlinear reconstruction performance of sparse representation in image compression and reconstruction process, a new image compression algorithm based on dual synthesis and analysis dictionaries is proposed. Firstly, the dual synthesis and analysis dictionaries learning algorithm is analyzed, including penalty function analysis and the algorithm of dictionary learning with gradient decent. Then, the compression model based on synthesis and analysis dictionaries is introduced and the properties of the model is also analyzed. Experimental results demonstrate that the proposed method outperforms many other algorithms in image compression.
引用
收藏
页码:79 / 85
页数:7
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