Remotely sensed image thresholding using OTSU & differential evolution approach

Remotely sensed images have detailed stored information spreaded over many spectral bands coving full Electromagnetic spectrum. This information needs to be carefully extracted based on the type of segmentation one is doing or on the type of objects to be classified. In this paper, segmentation of high resolution image is done through bi-level and multi-level thresholding techniques. For bi-level, traditional OTSU method is used and Differential Evolution with OTSU technique as its objective function is used for multi-level thresholding. Segmented results with both the techniques are shown and it is clearly seen that differential evolution with OTSU method yield better results.