Abstract:

From the shadow region properties, a new algorithm of shadow detection and compensation based on principal component analysis (PCA) is proposed for high resolution remote sensing images. The ratio between the original blue band and the first principal component is computed. Shadow and non-shadow regions are segmented using the histogram-thresholding method. A morphological algorithm is used to produce an accurate shadow mask, and a dilation operation is performed to find the surrounding homogeneous region of a shadow. Each shadow region is matched to its adjacent homogeneous region to achieve shadow compensation. Finally,image smoothing and inverse PCA transformation are performed on the compensated image. Experimental results show that the algorithm is effective.

Key words: remote sensing, principal component analysis, shadow detection, shadow compensation