Object Shadow Detection and Removal from Remotely Sensed Images
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 4
Abstract
In accordance with the characteristics of urban high-resolution color remote sensing images, we put forward an object shadow detection and removal method from remotely sensed images. In object shadow detection method, during image segmentation, shadow features are taken into consideration and after that using statistical feature of the images, suspected shadows are extracted. In our method, first color image is converted to gray image, after that global thresholding process is performed to detect the suspected shadow region. Next to that morphology erosion process is performed, then convolution filtering to elimination of false shadow and finally obtain coarse-shadow map, to classify the input color image into the candidate shadow pixels and the nonshadow pixels. After shadow detection, removal method used to remove shadow region to enhance the shadow images. Finally obtain recovered image. Experiments show that the new method can accurately detect shadows and remove from urban remote sensing images.
Authors and Affiliations
Atul A. Kolge, Yogita K. Dubey
Keywords
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