基于仿生模型的图像质量评价方法

侯伟龙; 高新波; 何立火; 高飞

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An image quality metric based on bionic models

首发时间：2011-08-29

HOU Weilong ¹
Weilong Hou, (1988-), male, received her B.S. degree in electronic information engineering from Xidian University, Xi\'an, China, in 2010. Now he is studying for the Ph.D. degree in Xidian University. His research interests include image quality assessment, human visual system. Currently, he works on visual attention mechanism.
GAO Xinbo ²
Xinbo Gao (1972-), male, is a Professor of Pattern Recognition and Intelligent System, and Director of the VIPS Lab, Xidian University. His research interests are computational intelligence, machine learning, computer vision, pattern recognition and wireless communications.
HE Lihuo ² GAO Fei ²

1、VIPS Lab and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, School of Electronic Engineering, Xidian University
2、VIPS Lab and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, School of Electronic Engineering, Xidian University, Xi'an 710071, P.R. China

Abstract：Image quality evaluation is to use some computational models to predict the quality of the specified image automatically and accurately. Since human eyes are ultimate receptor of images, it is better to mimic human visual system (HVS) to perceive the image quality. Based on the properties of the HVS, a novel bionic image quality metric (IQA) is proposed, which adopts several bionic characteristics, e.g. multi-channel decomposition, contrast sensitivity function, center-surround operation and lateral inhibition mechanism. Experimental results demonstrate that the performance of the proposed IQA method outperforms those of the existing methods.

keywords： Image Quality Assessment Human Visual System Visual Attention

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基于仿生模型的图像质量评价方法

侯伟龙 ¹
Weilong Hou, (1988-), male, received her B.S. degree in electronic information engineering from Xidian University, Xi\'an, China, in 2010. Now he is studying for the Ph.D. degree in Xidian University. His research interests include image quality assessment, human visual system. Currently, he works on visual attention mechanism.
高新波 ²
Xinbo Gao (1972-), male, is a Professor of Pattern Recognition and Intelligent System, and Director of the VIPS Lab, Xidian University. His research interests are computational intelligence, machine learning, computer vision, pattern recognition and wireless communications.
何立火 ³ 高飞 ³

1、西安电子科技大学电子工程学院影像系统实验室，西安电子科技大学智能感知与图像理解教育部重点实验室
2、西安电子科技大学电子工程学院影像系统实验室，西安电子科技大学智能感知与图像理解教育部重点实验室，陕西西安 710071
3、VIPS Lab and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, School of Electronic Engineering, Xidian University, Xi'an 710071, P.R. China

摘要：图像质量的客观评价是图像处理领域中的一个重要分支，其评价指标可以作为一种测度或者准则用来校准图像处理系统，抑或用于图像处理算法的优化及参数的优选。鉴于人眼是图像的最终受体，而视觉注意机制在人眼观看图像过程中起到非常重要的作用。因此本文针对图像质量评价的基本问题，提出了一种新的基于视觉注意机制的仿生学图像质量评价算法。结合视觉注意机制形成的原理，利用高斯塔式分解将图像分解为不同的空域尺度，从而模拟人类视觉系统的多通道特性。采用对比敏感度函数对不同的空域尺度进行视觉感知滤波，然后利用人类视觉系统的中央-周边感受野特性与侧抑制机制对图像特征进行提取，进而利用该特征来捕捉由图像降质引起的视觉感知的差异。实验结果表明，本方法能较准确地反映人眼对图像质量的主观感受，且计算复杂度较低，性能优于同类评价算法。

关键词：图像质量评价人类视觉系统视觉注意机制

基金：

1. Supported by the Ph.D. Programs Foundation of Ministry of Education of China （No. 20090203110002, 20090203120011）

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HOU Weilong,GAO Xinbo,HE Lihuo,et al. An image quality metric based on bionic models[EB/OL]. Beijing:Sciencepaper Online[2011-08-29]. https://www.paper.edu.cn/releasepaper/content/201108-500.

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论文编号	201108-500
论文题目	基于仿生模型的图像质量评价方法
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