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Height estimation for buildings in monocular satellite/airborne images based on fuzzy reasoning and genetic algorithm

This paper presents a height estimation method for buildings with polygonal footprints in monocular satellite/airborne images by combining fuzzy reasoning and genetic algorithm. A fitness function is employed using a set of fuzzy rules that asses various height hypothesis candidates for each building. A genetic algorithm is utilized that optimizes the fitness function to recover the most accurate height quickly with an accuracy that is independent of the acquisition method. Experimental results verify the effectiveness of the proposed method, with an overall mean height error of 35 cm.