Image Denoising Algorithm Based on PSO Optimizing Structuring Element
A new image denoising algorithm is proposed to deal with information loss in the conventional morphological image denoising process. The algorithm uses median operation to improve morphological operations’ performance, which called median closing operation. It gives a mathematical model of the structuring element unit (SEU) composed of a zero square matrix. The particle swarm optimization (PSO) algorithm is employed for choosing the size of structuring element. The value of peak signal to noise ratio (PSNR) is taken as a fitness function, and the transformed value of the particles position is taken as the size of the structuring element. Experimental results show that the denoising performance of the proposed algorithm has obvious superiority than conventional morphological algorithm. It can overcome the inherent deficiency of conventional morphological operations, adaptively obtain the size of the structuring element, and effectively remove impulse noise from images, especially for the image whose signal to noise ratio value is relatively low. So it has a good prospect in image processing.
Image Denoising Morphological Filter Particle Swarm Optimization (PSO) Structuring Element (SE) Peak Signal-to-noise Ratio (PSNR)
Zhu youlian Huang cheng
College of Electronic Information Engineering, Jiangsu Teachers University of Technology, Changzhou, China, 213001
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
2416-2420
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）