Image Enhancement Method Using Quantum Genetic Algorithm

This algorithm represents an image enhancement method grounded in quantum genetic algorithm principles. The implementation comprises multiple MATLAB .m sub-files designed to systematically improve image quality by optimizing enhancement parameters. The core innovation involves integrating quantum rotation gate technology, which performs nonlinear operations on image pixel values through rotational transformations. These quantum operations modulate pixel intensity distributions to enhance contrast and sharpness characteristics. The quantum rotation gate functions by applying rotational transformations to pixel values in quantum state representation, effectively adjusting brightness levels and color saturation through coherent superposition operations. By combining this quantum mechanism with genetic algorithm optimization, the method evolves optimal parameter combinations through selection, crossover, and mutation operations encoded in quantum chromosomes. The genetic algorithm component employs fitness functions evaluating image quality metrics to guide the evolutionary process toward superior enhancement outcomes. Key implementation aspects include quantum-bit encoding for solution representation, quantum gate operations for population evolution, and fitness evaluation functions assessing enhancement quality. This quantum-genetic hybrid approach demonstrates significant potential for advanced image processing applications, particularly in medical imaging, satellite imagery, and photographic enhancement domains where precise parameter optimization is crucial.