CAJ | 학술논문

针对传统图像增强方法存在的不足，提出了一种基于模拟退火遗传算法的图像增强算法。首先将图像增强过程参数编码成为遗传算法中的个体，然后通过模拟自然界生物进化过程对参数进行寻优，并引入模拟退火算法克服种群退化现象，同采用动态自适应交叉、变异过程防止局部最优解出现，最后根据找到的最优参数实现图像增强处理，并且采用仿真对比实验对算法有效性和优越性进行测试。仿真实验结果表明，相对于当前其它图像增强算法，模拟退火遗传算法可以恢复图像细节信息，提高了对比度，图像质量得到增强。
침대전통도상증강방법존재적불족，제출료일충기우모의퇴화유전산법적도상증강산법。수선장도상증강과정삼수편마성위유전산법중적개체，연후통과모의자연계생물진화과정대삼수진행심우，병인입모의퇴화산법극복충군퇴화현상，동채용동태자괄응교차、변이과정방지국부최우해출현，최후근거조도적최우삼수실현도상증강처리，병차채용방진대비실험대산법유효성화우월성진행측시。방진실험결과표명，상대우당전기타도상증강산법，모의퇴화유전산법가이회복도상세절신식，제고료대비도，도상질량득도증강。
In order to solve the defects of traditional image enhancement methods, this paper proposes an image enhancement algorithm based on simulated annealing and genetic algorithm. First of all, the image enhancement process parameters are encoded individual in genetic algorithm, secondly parameters are found by simulating natural e﹣volution optimization process, and the simulated annealing algorithm is introduced to overcome the population degrada﹣tion phenomenon, and the dynamic self-adaptive crossover, mutation process are used to prevent appearing local opti﹣mum solution, finally, the images are enhanced according to the optimal parameters, and the simulation experiment is used to test the validity and superiority of the algorithm. The simulation results show that compared to other image en﹣hancement algorithms, genetic simulated annealing algorithm can restore the image detail information, improve the contrast and the image quality.