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结合暗通道原理和双边滤波的遥感图像增强

周雨薇,陈强,孙权森,胡宝鹏(南京理工大学计算机科学与工程学院, 南京 210094;解放军理工大学气象海洋学院, 南京 211101)

摘 要
目的 在遥感应用如目视解译等任务中,需要提高遥感影像的视觉质量,为此提出一种基于暗通道原理和双边滤波的遥感图像增强算法。方法 由于暗通道模型的softmatting过程计算复杂性高,故使用双边滤波估计大气光幕,进而获得优化透射图,代替He算法中softmatting过程,提高了计算效率。针对将暗通道原理应用于遥感图像增强时所产生的色彩失真现象,提出透射图的改进算法,提高景深图像的取值,同时约束其最大值不大于1。最后,基于景深图像和暗通道原理获得增强后的遥感图像。结果 实验结果表明,本文算法能够有效地增加图像的对比度。与基于双边滤波单尺度Retinex图像增强、四尺度Retinex增强、直方图均衡化及MSRCR增强的结果进行了比较,实验结果验证了算法的有效性。结论 本文模型能够使处理后的遥感图像更符合视觉特性,以便于目视解译与分析。该算法适用于遥感图像的可视化增强。
关键词
Remote sensing image enhancement based on dark channel prior and bilateral filtering

Zhou Yuwei,Chen Qiang,Sun Quansen,Hu Baopeng(The School of Computer Science and Engineering, Nanjing University of Science & Technology, Nanjing 210094, China;Institute of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China)

Abstract
Objective In remote sensing applications such as visual interpretation, it is necessary to improve the visual quality of remote sensing image. An approach based on dark channel prior and bilateral filtering is proposed for the enhancement of remote sensing image. Method To address the high computational complexity of softmatting in the dark channel prior model, bilateral filtering is used to estimate the atmospheric veil,then obtain the refined transformation map of He's model. Crossing-color is observed when dark channel prior is applied to the enhancement of remote sensing images. Thus, an improved algorithm for calculating the transmission map is presented by improving the pixel values of depth image and making all pixel values not larger than one. Finally, the enhanced remote sensing image is obtained with depth images and dark channel prior model. Result Experimental results demonstrate that the proposed algorithm can increase the image contrast effectively. Comparing to the image enhancement models based on SSR and bilateral filtering, Four-Scale Retinex, histogram equalization and MSRCR, the results validates the effectiveness of the proposed algorithm. Conclusion The proposed model can make enhanced remote sensing images more acceptable in line with the visual characteristics and more convenient for visual interpretation, and it is feasible for the remote sensing image visualization enhancement.
Keywords
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