Ling Ding^{1, 2}, Huyin Zhang^{1, *}, Jinsheng Xiao³, Junfeng Lei³, Fang Xu³, Shejie Lu²

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 675-690, 2020, DOI:10.32604/cmes.2020.07987

Abstract The ultimate goal of image denoising from video is to improve the given image, which can reduce noise interference to ensure image quality. Through denoising technology, image quality can have effectively optimized, signal-to-noise ratio can have increased, and the original mage information can have better reflected. As an important preprocessing method, people have made extensive research on image denoising algorithm. Video denoising needs to take into account the various level of noise. Therefore, the estimation of noise parameters is particularly important. This paper presents a noise estimation method based on variance stability transformation, which estimates the parameters of variance stability… More >

Manyu Jin¹, Tao Wang¹, Zexuan Ji^1,*, Xiaobo Shen²

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 501-515, 2018, DOI: 10.3970/cmc.2018.02371

Abstract Perceptual image quality assessment (IQA) is one of the most indispensable yet challenging problems in image processing and computer vision. It is quite necessary to develop automatic and efficient approaches that can accurately predict perceptual image quality consistently with human subjective evaluation. To further improve the prediction accuracy for the distortion of color images, in this paper, we propose a novel effective and efficient IQA model, called perceptual gradient similarity deviation (PGSD). Based on the gradient magnitude similarity, we proposed a gradient direction selection method to automatically determine the pixel-wise perceptual gradient. The luminance and chrominance channels are both took… More >