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In this project, an object-based approach for urban land covers classification from high resolution satellite image using Fuzzy logic. OBIA analysis of image segmentation that is, clustering of pixels into homogenous objects, and subsequent classification or labelling of the objects, and modelling based on the characteristics of objects is done using MATLAB GUI model. When applied to a satellite image, the fuzzy logic approach involves three steps. First, a membership function is computed for each pixel and each class. This membership function expresses the likelihood that the measured radiance belongs to a class with a known reflectance distribution. Thus, for each pixel, class memberships are assigned to the predetermined classes on the basis of the derived membership functions. Second, three variables are retrieved from each of the classspecific algorithms for which the pixel has membership. Third, the class memberships are used to weight the class-specific retrievals to obtain a final blended retrieval for each pixel. The algorithm was implemented in MATLAB GUI model and was tested on remotely sensed images of different sensors, resolutions and complexity levels.

Implementation of Fuzzy Logic for the High-Resolution Remote Sensing Images with Improved Accuracy