IMAGE FUSION AND RECOGNITION BASED ON COMPRESSED SENSING THEORY

被引：11

作者：

Bai, Qiuchan ^{[1
]}

Jin, Chunxia ^{[2
]}

机构：

[1] Huaiyin Inst Technol Huai, Fac Elect & Elect Engn, Huaian 223003, Peoples R China

[2] Huaiyin Inst Technol Huai, Fac Comp Engn, Huaian 223003, Peoples R China

来源：

INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS | 2015年 / 8卷 / 01期

关键词：

Mage fusion; target recognition; compressed sensing; wavelet transform;

D O I：

10.21307/ijssis-2017-753

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

As the compressed sensing theory can offer a better performance than Nyquist sampling theorem when dealing with large amounts of data, it becomes very popular for image fusion and target recognition in image processing. In this paper, a new image fusion algorithm based on compressed sensing was proposed. By discrete cosine transform, it fused images through weighted coefficient, recovered the fusion images by basic pursuit algorithm. Moreover, a recognition algorithm in compressed sensing was also studied, which obtained a sample matrix using preprocessing based on a wavelet transform, calculated the approximate coefficient by orthogonal matching pursuit, and made a classification using the with minimum distance formula. Finally, experiments were designed to demonstrate the effectiveness of the proposed algorithms.

引用

页码：159 / 180

页数：22

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