Fractional order differentiator based edge detection in remote sensing images

Urban object detection places a vital role in urban planning and development. The edge detection algorithms are useful and efficient to perform the object detection. A new edge detection algorithm has been presented in this manuscript. The proposed edge detection algorithm used Chebyshev polynomial based fractional order differentiator. The convolution operation has been performed with fractional order differentiator. The Canny edge detection method has been applied on the convoluted image. The algorithm has been validated with the benchmark data set provided by International Society for Photogrammetry and Remote Sensing (ISPRS) set working group.