Enhanced Genetic Algorithm in Image Reconstruction

Genetic Algorithm (GA) is a widely used and popular evolutionary algorithm to solve combinatorial optimization problems. It is inspired by Darwin’s survival of the fittest theory in nature. This work reviews of the metaheuristic approaches in the domain of image processing, with specific focus on the application of Genetic Algorithm (GA) for image reconstruction and comparatively analyzes the past works related to the algorithm’s application in the image processing domain. The literature review shows that there are many potential improvements in the key operators of this algorithm in selection, crossover and mutation that can be further enhanced, and thus proposes a future study into the speed performance improvement of GA in finding the best solution by applying it in image reconstruction. This work is intended to identify and justify the improvements proposed for the future study, in order to enhance the unambiguousness of the reconstructed image and to reduce the time needed to reconstruct the image.