Paper Info
Title
Shadow Detection and Compensation in High Resolution Satellite Image Based on Retinex
Abstract
In this paper, shadow detection and compensation are treated as image enhancement tasks. The principal components analysis (PCA) and luminance based multi-scale 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.
Year
DOI
Venue
2009
10.1109/ICIG.2009.56
ICIG
Keywords
DocType
ISBN
shadow region,motion compensation,image enhancement task,high resolution satellite image,luminance channel,shadow detection image,original image,retinex,principal components abalysis,shadow detection,lmsr technique,shadow compensation,final shadow compensation image,enhanced image,principal components analysis,image enhancement,principal component analysis,luminance based multi-scale retinex algorithm,inverse transform,histogram threshold technique,principal component
Conference
978-1-4244-5237-8
Citations 
PageRank 
References 
5
0.51
5
Authors
2
Name
Order
Citations
PageRank
Shugen Wang1123.57
Yue Wang2960143.63