BLURRED IMAGE RESTORATION USING GENETIC ALGORITHM
Abstract
The Genetic Algorithm models are becoming very attractive in image processing where high computational performance is required. This paper describes a genetic algorithm for blurred image, which is designed and estimated using Matrix R3 x3. The genetic algorithm takes random strings as an input in binary code and uses one point crossover between two random strings and uses mutation after many generations. The output is restorated matrix R3 x3 according to mask size, The computer test shows that the restorated images have better visual properties compared with inverse filter
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