Advanced Q-NLM Algorithm Application In Image Enoising

The quanlity of the digital image which is essential in daily life is requested toimprove. The veracity of digital image is very important in Medical images, licenseplates, and aerial images. The image noise filtering before the using of image isimportant part of Image extraction for the different types of noise pollution in thegeneration, transmission and terminal extraction process due to the equipment’simperfection.In this paper, the merit and demerit of impulse noise and gaussian noisedenoising have been studied. We get a new research and application in removing themixed noise which is based on nonlocal algorithm of quotient by combining theadvantages of both, and it’s called advanced Q-NLM algorithm application in medicalimage denoising. For nonlocal average algorithm does not adapt to traditional impulsenoise denoising problems, we put forward the concept of degree of pixels from thegroup of Q. The degree of pixels from the group of Q value is used to determine theoriginal pixel similarity with impulsive noise, then dividing pixel area on the basis ofdegree of pixels from the group of Q.We reduce the effects of mixed noise in filteringof image by adjusting the threshold and different regions of the introduction ofmedian filter to remove impulse noise point. Simulation experiments’ results showthat the combination outlier degree mixed with nonlocal average algorithm inremoving noise can improve the image SNR and retain the image details effectively.