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用于弱目标检测的形态滤波和小波变换图像增强算法

吉书鹏 丁小青

吉书鹏, 丁小青. 用于弱目标检测的形态滤波和小波变换图像增强算法[J]. 红外技术, 2003, 25(4): 32-38. doi: 10.3969/j.issn.1001-8891.2003.04.008
引用本文: 吉书鹏, 丁小青. 用于弱目标检测的形态滤波和小波变换图像增强算法[J]. 红外技术, 2003, 25(4): 32-38. doi: 10.3969/j.issn.1001-8891.2003.04.008
JI Shu-peng, DING Xiao-qing. Morphological Filters and Wavelet-based Histogram Equalization Image Enhancement for Weak Target Detection[J]. Infrared Technology , 2003, 25(4): 32-38. doi: 10.3969/j.issn.1001-8891.2003.04.008
Citation: JI Shu-peng, DING Xiao-qing. Morphological Filters and Wavelet-based Histogram Equalization Image Enhancement for Weak Target Detection[J]. Infrared Technology , 2003, 25(4): 32-38. doi: 10.3969/j.issn.1001-8891.2003.04.008

用于弱目标检测的形态滤波和小波变换图像增强算法

doi: 10.3969/j.issn.1001-8891.2003.04.008
详细信息
  • 中图分类号: TN216

Morphological Filters and Wavelet-based Histogram Equalization Image Enhancement for Weak Target Detection

  • 摘要: Image enhancement methods are typically aimed at improvement of the overall visibility of features. Though histogram equalization can enhance the contrast by redistributing the gray levels, it has the drawback that it reduces the information in the processed image. In this paper, we present a new image enhancement algorithm. After histogram equalization is carried out, morphological filters and wavelet-based enhancement algorithm is used to clean out the unwanted details and further enhance the image and compensate for the information loss during histogram equalization. Experimental results show that the morphological filters and wavelet-based histogram equalization algorithm can significantly enhance the contrast and increase the information entropy of the image.
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