基于压缩感知的图像配准算法研究

针对SIFT算法的图像配准耗时长的问题, 提出一种基于压缩感知的图像配准算法。首先, 使用FAST算法提取图像角点, 然后, 使用SIFT算法生成角点描述子并使用压缩感知原理降维, 最后, 使用双向匹配算法进行匹配。通过实验数据分析, 基于压缩感知的图像配准算法在图像配准准确度方面与传统SIFT算法、传统SURF算法、文献

Abstract

Aiming at the time consuming problem of image registration of SIFT algorithm, an image registration algorithm based on compressed sensing was proposed. Firstly, the image corner was extracted by FAST algorithm, then, the SIFT algorithm was used to generate the corner descriptor and the compressed sensing principle was used to reduce the dimension of the corner descriptor. Finally, a bidirectional matching algorithm was used to match. Through the experimental data analysis, image registration algorithm based on compressed sensing is nearly the same in image registration accuracy in comparison with the traditional SIFT algorithm、the traditional SURF algorithm、reference

参考文献

[1] 算法、文献

[2] 算法、文献

[3] 算法相当, 但在图像配准耗时方面分别缩短了71.21%、44.45%、54.57%、54.96%、13.40%, 验证了该算法的实时性和有效性。

[4] algorithm、reference

[5] algorithm、reference

[6] algorithm, but time consuming of image registration is decreased by 71.21%、44.45%、54.57%、54.96%、13.40%, verifying the instantaneity and effectiveness of the algorithm.

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章盛, 李培华, 张骏, 钱名思, 鲁兴平, 叶程广. 基于压缩感知的图像配准算法研究[J]. 光电子技术, 2018, 38(2): 111. ZHANG Sheng, LI Peihua, ZHANG Jun, QIAN Mingsi, LU Xingping, YE Chengguang. Research on Image Registration Algorithm Based on Compressed Sensing[J]. Optoelectronic Technology, 2018, 38(2): 111.

基于压缩感知的图像配准算法研究

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