计算机工程与应用2017，Vol.53Issue(7)：202-205,4.DOI:10.3778/j.issn.1002-8331.1509-0017
基于小波域峰态值的无参考噪声图像评价算法
Blind noisy image quality assessment algorithm based on wavelet kurtosis
摘要
Abstract
Noise distortions introduced in natural images generally break the initial probability distributions by dispersing image pixels randomly. It finds that there exists a big difference between the distributions of Discrete Wavelet Transform (DWT)coefficients of natural images and noisy images:for natural images, their distributions are sharp with highpeaked-ness and slight tail;for noisy images, the shapes are much flatter with lower peakedness and heavier tail. Kurtosisis able to measure and differentiate the probability distributions of noisy images with various noise levels. Moreover, the kurtosis values of DWT coefficients are stable for varyingfrequency filters. This paper proposes a Blind NoisyImage Quality Assessment model using Kurtosis(BNIQAK). Five types of noisy images in the three biggest databases are taken for testing BNIQAK. Experimental results show that BNIQAK has better evaluation performance compared with existing blind noisy models, as well as some general blindand Full-Reference(FR)methods.关键词
无参考噪声图像质量评价/离散小波变换/峰态值Key words
blind noisy image quality assessment/discrete wavelet transform/kurtosis分类
信息技术与安全科学引用本文复制引用
吕风杰,信科..基于小波域峰态值的无参考噪声图像评价算法[J].计算机工程与应用,2017,53(7):202-205,4.基金项目
山东省自然科学基金(No.ZR2014FL005) （No.ZR2014FL005）
山东省教育厅科技发展项目(No.J08LJ52). （No.J08LJ52）
