Variational adaptive image denoising model based on human visual system

Wenjun Li; Chanjuan Liu; Hailin Zou

doi:10.1117/12.901576

8 December 2011 Variational adaptive image denoising model based on human visual system

Wenjun Li, Chanjuan Liu, Hailin Zou

Author Affiliations +

Proceedings Volume 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis; 80020X (2011) https://doi.org/10.1117/12.901576
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

A variational image adaptive denoising model based on human visual system is proposed by introducing control parameter p which can determine the diffusion intensity to Total Variation (TV) model. The model can adaptively select the value of parameter p according to human visual system noise visibility value of each pixel which makes diffusion intensity close to edges smaller than those far away from edges. For this method is more consistent with human perception, human eyes can perceive the improvement of image quality intuitively. Numerical experiments show that the proposed method can overcome staircase effect, remove the noise while preserving significant image details and better performance has been achieved.

Citation Download Citation

Wenjun Li, Chanjuan Liu, and Hailin Zou "Variational adaptive image denoising model based on human visual system", Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80020X (8 December 2011); https://doi.org/10.1117/12.901576

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