| Image processing can be regarded as a kind of image processing technology, and it established the foundation for image analysis and higher level of image understanding. As an important branch of preconditioning section in image processing, image enhancement can meet the current needs in the areas of multimedia technology development and research by improving the quality of the image, highlighting the ROI information of an image. The paper summarizes the research status of image enhancement technology by analyzing the space domain, frequency domain and optimization theory of image enhancement technology, and studies the theory and algorithm of image enhancement processing, and combines and improves the three algorithms, which is traditional genetic algorithm, particle swarm optimization algorithm and fuzzy enhancement algorithm, then enhancement the traditional statues image and medical image processing using the method based on optimization theory algorithm.The main research and works as follows:(1) On the basis of the combination of the traditional particle swarm optimization algorithm and the fuzzy enhancement algorithm, an image fuzzy enhancement algorithm based on improved particle swarm optimization is proposed in this paper. By introducing the principle of symmetry distribution in the particle space and the tabu search algorithm, the paper solves the problem that traditional particle swarm optimization algorithm is easy to fall into local optimal solution, and the operation time is too long after the combination with the traditional fuzzy enhancement algorithm. And improved the accuracy of the algorithm by promote the traditional one-dimensional particle swarm optimization to two-dimensional, while searching for the traditional fuzzy enhancement algorithm in two fuzzy parameters Fp and Fe. Ultimately, by combining the improved particle swarm optimization algorithm and fuzzy enhancement algorithm, the article realized the image fuzzy enhancement.(2) On the basis of the combination of the traditional genetic algorithm and the fuzzy enhancement algorithm, an image fuzzy enhancement algorithm based on improved two dimensional hybrid genetic algorithm is proposed in this paper. The method proposed in this paper solves the shortcomings of the traditional operation and fully considers the evolution characteristics of individual particles in the population, by modifying the three operation modes of the genetic algorithm from the traditional constant probability to the modified form of the population evolution algebra. What’s more, by combining with the improved two-dimensional particle swarm optimization algorithm, the algorithm is improved and the optimal solution value of the problem space is approached, and by modifying the traditional fuzzy characteristic function formula and using the fuzzy parameter Fp and the maximum gray value of the image, the formula of different fuzzy characteristic function is adjusted, and the problem of image gray level information loss in the traditional fuzzy enhancement algorithm is solved. Ultimately, the combination of improved two-dimensional hybrid genetic algorithm and improved fuzzy enhancement algorithm, the article realized the image fuzzy enhancement.Eventually, experimental results of the proposed algorithms and traditional compared to the fuzzy enhancement algorithm based on optimization theory of image, the proposed paper not only takes into account the optimization algorithms and their characteristics and realize the effective combination, and through considering the fuzzy characteristics of the image itself on the image of fuzzy enhancement to improve the image quality, the image contrast and bring more edge information and details of the image. |
