摘要
将免疫粒子群优化算法和非完全Beta函数结合,提出了一种自适应图像对比度增强方法。该免疫粒子群优化算法结合了粒子群优化算法具有的全局寻优能力和免疫系统的免疫信息处理机制,改善了粒子群优化算法摆脱局部极值点的能力。利用免疫粒子群优化算法自动搜索最佳的灰度变换参数,从而获得一条最佳的灰度变换曲线,实现对图像进行全局增强处理。实验结果表明,该算法不仅能有效地提高图像整体对比度和视觉效果,而且适合图像的自动化处理。
A new kind of image adaptive contrast enhancement approach based on particle swarm optimization algorithm and incomplete Beta function is given. The proposed algorithms have both the properties of original particle swarm optimization algorithm and the immune mechanism of immune system, can improve the abilities of approaching the global excellent result. The optimal gray transformation parameters are obtained using the particle swarm optimization algorithm with immunity. Thus an optimal gray transformation curve is obtained and global contrast enhancement is done to the input image based on the optimal gray transformation curve. The results show that the new approach enhance the global contrast of the image effectively and vision.
出处
《计算机工程与设计》
CSCD
北大核心
2007年第20期4959-4961,共3页
Computer Engineering and Design
基金
国家自然科学基金项目(60573179)
