关键词: 无参考噪声图像质量评价, 离散小波变换, 峰态值

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 highpeakedness 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.

Key words: blind noisy image quality assessment, discrete wavelet transform, kurtosis