In image processing and pattern recognition, edge detection is used to preserve the structural properties in an image which significantly reduces the amount of data and also filters out the useless information. Edge detection is an important area in processing the satellite images which are of high resolution with lot of information. Bi-level Bi-stage concept has been used to detect the edges based on global and local threshold values in Shannon entropy Multi thresholding (SMT) method for gray

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... cale images. To extend this concept for multispectral images, a Shannon entropy Multispectral Multi Thresholding (SM 2 T) algorithm has been proposed. Even though this method detects more edges than SMT, Edge Detection using Multispectral thresholding (EDMST) method, based on Otsu thresholding values for multispectral images, detects more edges than SM 2 T method. Bi-level Bi-stage Multispectral thresholding (B 2 MST) algorithm has also been proposed based on global and local Otsu thresholding values to improve the EDMST method. Even though all the methods are applied on natural, art and simulated images, the performance is evaluated on simulated images, due to the existence of well known edges. The result of SMT, SM 2 T, EDMST and B 2 MST methods have been compared based on human visual system, number of edges detected and F-measure. Finally it has been observed that the B 2 MST shows better results and hence applied on satellite images.