Object Shadow Detection and Removal from Remote Sensing Images using Successive Thresholding Method - Sonvane, Sadhana R; UB , olapurkar (International Journal of Computer Sciences and Engineering, 2019)
Now a day’s capturing a live images with high quality plays an crucial role in all the fields. It is more important as far as security in military, commercial, household fields as well as to monitor the continuous changes in earth surfaces are concern. Most of the time to achieve clear images we have to differentiate between original object and shadow as detecting objects under the influence of shadow is a challenging task. In urban area the shadow produces artificial color features and shape deformation of objects which decays the quality of image. Shadow mainly occurs due to elevate objects and If light source has been blocked by some obstacles. However, a lot of shadowed areas in remote sensing images of urban areas have affected the tasks, such as image classification, object detection and recognition. Tsai presented an efﬁcient algorithm which uses the ratio value of the hue over the intensity to construct the ratio map for detecting shadows of color aerial images. Instead of only using the global thresholding process in Tsai’s algorithm, this paper presents a novel successive thresholding scheme (STS) to detect shadows more accurately. By performing the global thresholding process on the modiﬁed ratio map, a coarse-shadow map is constructed to classify the input color aerial image into the shadow pixels and the non-shadow pixels. Instead of only using the global thresholding process in Tsai’s algorithm, this paper presents a novel successive thresholding scheme (STS) to detect shadows more accurately. For the three four testing images, which contain some low brightness objects, our proposed algorithm has better shadow detection accuracy when compared with the previous shadow detection algorithms proposed by Tsai. Thus for the correct image interpretation it is important to detect shadow regions and restore their information. So it is very essential to detect the shadow regions and remove it effectively to get useful information with good quality.