Shadow Detection and Compensation in High Resolution Satellite Image Based on Retinez
In this paper, shadow detection and compensation are treated as image enhancement tasks. The principal components analysis (PCA) and luminance based multiscale Retinex (LMSR) algorithm are explored to detect and compensate shadow in high resolution satellite image. PCA provides orthogonally channels, thus allow the color to remain stable despite the modification of luminance. Firstly, the PCA transform is used to obtain the luminance channel, which enables us to detect shadow regions using histogram threshold technique. After detection, the LMSR technique is used to enhance the image only in luminance channel to compensate for shadows. Then the enhanced image is obtained by inverse transform of PCA. The final shadow compensation image is obtained by comparison of the original image, the enhanced image and the shadow detection image. Experiment results show the effectiveness of the proposed method.
shadow detection shadow compensation principal components abalysis Retinez high resolution satellite image
Shugen Wang Yue Wang
State Key laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing School of School of Remote Sensing and Information Engineering Wuhan University Wuhan, China
国际会议
The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)
西安
英文
209-212
2009-09-20（万方平台首次上网日期，不代表论文的发表时间）