[1]王宇庆.基于梯度复数矩阵的图像质量客观评价方法[J].计算机技术与发展,2013,(01):63-66.
　WANG Yu-qing.Objective Image Quality Assessment Based on Gradient Complex Matrix[J].,2013,(01):63-66.
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基于梯度复数矩阵的图像质量客观评价方法()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年01期
页码:
63-66
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Objective Image Quality Assessment Based on Gradient Complex Matrix
文章编号:
1673-629X（2013）01-0063-04
作者:
王宇庆
中国科学院长春光学精密机械与物理研究所中国科学院航空光学成像与测量重点实验室
Author(s):
WANG Yu-qing
关键词:
梯度; 复数矩阵; 图像质量评价; 奇异值分解; 人类视觉系统
Keywords:
gradient; complex matrix; image quality assessment; singular value decomposition; human visual system
文献标志码:
A
摘要:
将灰度图像的梯度信息作为表征图像结构信息的一个重要特征,进一步提高了图像质量客观评价结果与主观评价结果的一致程度,增强了人眼敏感的图像边缘信息.对梯度复数矩阵进行奇异值分解,计算得到相应的奇异值特征向量,通过计算参考图像与降质图像对应分块复数矩阵奇异值特征向量的相似程度得到了降质图像的量化质量评价结果.实验表明,梯度信息更能突出图像的结构特征,所提方法优于传统 MSE 及 MSVD 方法,与人眼视觉特性的一致性较好
Abstract:
Structural information was described by gradient to improve the consistency of objective image assessment method with subjec-tive method. The effect of the edge structure in the image quality was emphasized accordingly. Singular value decomposition was per-formed on gradient distribution complex matrix. The similarity of the singular vectors of the reference image and the distorted image was used to measure the structural similarity of the two images. Then the numerical quality assessment results were achieved. Result from ex-periments shows that the gradient distribution can emphasize the edge information. The proposed method is better consistent with human visual system characteristics than MSE and MSVD method based on simple pixel value distribution

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更新日期/Last Update: 1900-01-01