Abstract
The research of anomaly target detection algorithm in hyperspectral imagery is a hot issue, which has important research value. In order to overcome low efficiency of current anomaly target detection in hyperspectral image, an anomaly detection algorithm for hyperspectral images based on wavelet transform and sparse representation was proposed. Firstly, two-dimensional discrete wavelet transform is used to denoise the hyperspectral image, and the new hyperspectral image data are obtained. Then, the results of anomaly target detection are obtained by using sparse representation theory. The real AVIRIS hyperspectral imagery data sets are used in the experiments. The results show that the detection accuracy and false alarm rate of the propoesd algorithm are better than RX and KRX algorithm.
Highlights
In the 21 century, there has been rapid development in the field of remote sensing with the continuous improvement of human ability to understand the material world
The anomaly target detection has become a hot spot in recent years
A new anomaly detection algorithm for hyperspectral image is proposed for Wavelet Transform and Sparsity Representation (WTSR), which is simulated and distinguished by the real hyperspectral images
Summary
In the 21 century, there has been rapid development in the field of remote sensing with the continuous improvement of human ability to understand the material world. Satellite is constantly being launched for military and civilian services with high resolution imagers to ground imaging. China has launched high resolution 4 satellite, high resolution 5 satellite and other satellites. Hyperspectral image processing includes theoretical analysis, algorithm research and practical application. The algorithm research mainly focuses on hyperspectral image correction, hyperspectral image fusion, hyperspectral image classification, hyperspectral image pixel unmixed and hyperspectral image target detection. The anomaly target detection has become a hot spot in recent years. Process three-dimensional hyperspectral image, and the accuracy of anomaly target detection is high. Several existing algorithms for hyperspectral image are compared and analyzed. A new anomaly detection algorithm for hyperspectral image is proposed for Wavelet Transform and Sparsity Representation (WTSR), which is simulated and distinguished by the real hyperspectral images
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