Shadow detection in color aerial images based on HSI space and color attenuation relationship

TLDR: A new algorithm by which shadows are extracted from a single color aerial image is presented, which presents better shadow detection accuracy in the images that contain some dark green lawn, river, or low brightness shadow regions.

Abstract: Many problems in image processing and computer vision arise from shadows in a single color aerial image. This article presents a new algorithm by which shadows are extracted from a single color aerial image. Apart from using the ratio value of the hue over the intensity in some state-of-the-art algorithms, this article introduces another ratio map, which is obtained by applying the saturation over the intensity. Candidate shadow and nonshadow regions are separated by applying Otus’s thresholding method. The color attenuation relationship that describes the relationship between the attenuation of each color channel is derived from the Planck’s blackbody irradiance law. For each region, the color attenuation relationship and other determination conditions are performed iteratively to segment it into smaller sub-regions and to identify whether each sub-region is a true shadow region. Compared with previous methods, the proposed algorithm presents better shadow detection accuracy in the images that contain some dark green lawn, river, or low brightness shadow regions. The experimental results demonstrate the advantage of the proposed algorithm.