Image quality assessment using log-Gabor Weber feature

LU Yan-fei; ZHANG Tao; ZHANG Cheng

doi:10.3788/OPE.20152311.3259

您当前的位置：

首页 >

文章列表页 >

Image quality assessment using log-Gabor Weber feature

更新时间：2020-08-13

- Image quality assessment using log-Gabor Weber feature
- Optics and Precision Engineering Vol. 23, Issue 11, Pages: 3259-3269(2015)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院大学北京,中国,100049
  3. 中国科学院苏州生物医学工程技术研究所,江苏苏州,中国,215163
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152311.3259
  CLC： TP391.4
- Received：06 March 2015，
  
  Revised：16 April 2015，
  
  Published：25 November 2015
- 稿件说明：
移动端阅览
卢彦飞, 张涛, 章程. 应用log-Gabor韦伯特征的图像质量评价[J]. 光学精密工程, 2015,23(11): 3259-3269

LU Yan-fei, ZHANG Tao, ZHANG Cheng. Image quality assessment using log-Gabor Weber feature[J]. Editorial Office of Optics and Precision Engineering, 2015,23(11): 3259-3269
卢彦飞, 张涛, 章程. 应用log-Gabor韦伯特征的图像质量评价[J]. 光学精密工程, 2015,23(11): 3259-3269 DOI： 10.3788/OPE.20152311.3259.

LU Yan-fei, ZHANG Tao, ZHANG Cheng. Image quality assessment using log-Gabor Weber feature[J]. Editorial Office of Optics and Precision Engineering, 2015,23(11): 3259-3269 DOI： 10.3788/OPE.20152311.3259.

摘要

考虑人眼对亮度的感知符合韦伯定律的特点

本文利用log-Gabor滤波器模拟人眼对图像的感知过程

提出了一种新的log-Gabor韦伯特征

以便保留不同尺度的符合人眼感知的结构信息。基于此

还提出了一种应用log-Gabor韦伯特征的图像质量评价方法。首先将待评价失真图像和参考图像从RGB空间转换到YIQ颜色空间

分离亮度分量和颜色分量。然后利用log-Gabor韦伯特征和梯度特征计算亮度分量失真

并结合颜色分量的失真

得到失真图像与参考图像的局部相似度图。最后利用修正的CSF函数

对局部相似度图进行加权

得到图像质量评价指标。在LIVE、CSIQ和IVC3个图像库上的实验结果表明

本文方法与人眼主观感知有很好的一致性

而且相对于其他方法

表现更加稳定。本文方法在3个图像库上的加权Spearman秩相关系数(SROCC)为0.9498

Kendall秩相关系数(KROCC)为0.8026

Pearson线性相关系数(PLCC)为0.9438

相比对比方法有显著的提高。

Abstract

As human eye perception for the brightness accords with the Weber's law

this paper uses the log Gabor filter to simulate the human eye perception for an image and proposes a new log Gabor Weber characteristics to keep the structural information interested by human for different scales. To assess the image quality more effectively

a new image quality assessment method was proposed by using log-Gabor Weber feature. The log-Gabor filter and Weber's law were used to obtain a new feature named log-Gabor Weber feature(LGW). Firstly

the distorted image and reference image were transformed from the RGB color space into a YIQ color space to separate the luminance component and the chromatic component. Then

the LGW feature and gradient feature were used to calculate the distortion of luminance component. Furthermore

the distortion of chromatic component was integrated to get the local similarity map between distorted image and reference image. Finally

a modified CSF pooling strategy was applied to the overall local similarity map to obtain the final image quality index. The experimental results on three benchmark image databases

LIVE

CSIQ and IVC

indicate that the proposed method owns a good consistency with human subjective perception and it has a more stable performance as compared with other state-of-the-art methods. The weighted Spearman Rank Order Correlation Coefficient(SROCC)

Kendallrank-order Correlation Coefficient(KROCC) and the Pearsonlinear Correlation Coefficient

PLCC) values on three databases by the proposed method are 0.9498

0.8026 and 0.9438

respectively

which notably outperform other methods.

关键词

Keywords

references

SHEIKH H R, SABIR M F, BOVIK A C. A statistical evaluation of recent full reference image quality assessment algorithms[J]. IEEE Transactions on Image Processing, 2006, 15(11):3443-3452.

范媛媛,沈湘衡,桑英军. 基于对比度敏感度的无参考图像清晰度评价[J]. 光学精密工程,2011,19(10):2485-2493. FAN Y Y, SHEN X H, SANG Y J. No reference image sharpness assessment based on contrast sensitivity[J]. Opt. Precision Eng., 2011, 19(10):2485-2493.(in Chinese)

DAMERA-VENKATA N,KITE T D, GEISLER W S, et al.. Image quality assessment based on a degradation model[J]. IEEE Transactions on Image Processing, 2000, 9(4):636-650.

CHANDLER D M, HEMAMI S S. VSNR:A wavelet-based visual signal-to-noise ratio for natural images[J].IEEE Transactions on Image Processing, 2007, 16(9):2284-2298.

WANG Z, BOVIK A C, SHEIKH H R,et al.. Image quality assessment:from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 2004, 13(4):600-612.

WANG Z, SIMONCELLI E P, BOVIK A C. Multiscale structural similarity for image quality assessment[C]. IEEE Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, 2003:1398-1402.

WANG Z, LI Q. Information content weighting for perceptual image quality assessment[J]. IEEE Transactions on Image Processing, 2011, 20(5):1185-1198.

SHEIKH H R, BOVIK A C, VECIANA G. An information fidelity criterion for image quality assessment using natural scene statistics[J].IEEE Transactions on Image Processing, 2005, 14(12):2117-2128.

SHEIKH H R, BOVIK A C. Image information and visual quality[J].IEEE Transactions on Image Processing, 2006, 15(2):430-444.

ZHANG L, ZHANG L, MOU X Q, et al.. FSIM:A feature similarity index for image quality assessment[J]. IEEE Transactions on Image Processing, 2011, 20(8):2378-2386.

LIU A, LIN W, NARWARIA M. Image quality assessment based on gradient similarity[J]. IEEE Transactions on Image Processing, 2012, 21(4):1500-1512.

ZHANG L, SHEN Y, LI H Y. VSI:A visual saliency-induced index for perceptual image quality assessment[J]. IEEE Transactions on Image Processing, 2014, 23(10):4270-4281.

王宇庆,朱明. 评价彩色图像质量的四元数矩阵最大奇异值方法[J]. 光学精密工程,2013,21(2):469-478. WANG Y Q, ZHU M. Maximum singular value method of quaternion matrix for evaluating color image quality[J]. Opt. Precision Eng., 2013, 21(2):469-478.(in Chinese)

FIELD D J. Relations between the statistics of natural images and the response properties of cortical-cells[J].Journal of the Optical Society of America A A-Optics Image Science and Vision, 1987, 4(12):2379-2394.

CHEN J, SHAN S, HE C,et al.. WLD:A robust local image descriptor[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(9):1705-1720.

MANNOSJ L, SAKRISON D J. The effects of a visual fidelity criterion on the encoding of images[J]. IEEE Transactions on Information Theory, 1974,20(4):526-536.

SHEIKH H R, WANG Z, CORMACK L,et al.. LIVE image quality assessment database,release 2[OL/EB]. Available:http://live.ece.utexas.edu/research/quality.

Final Report From the Video Quality Experts Group on the Validation of Objective Models of Video Quality Assessment, Phase II VQEG[OL/EB]. Available:http://www.vqeg.org/.

程光权,张继东,成礼智,等. 基于几何结构失真模型的图像质量评价研究[J]. 自动化学报,2011,37(7):811-819. CHENG G Q, ZHANG J D, CHENG L ZH, et al.. Image quality assessment based on geometric structural distortion model[J]. ACTA AUTOMATIC SINICA, 2011, 37(7):811-819.(in Chinese)

LARSON C, CHANDLER D M. Categorical Image Quality(CSIQ) Database 2009[OL/EB]. Available:http://vision.okstate.edu/csiq.

NINASSI A, LECALLET P, AUTRUSSEAU F. Subjective Quality Assessment IVC Database 2005[OL/EB]. Available:http://www2.irccyn.ecnantes.fr/ivcdb.

Views

388

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Adaptive focusing evaluation algorithm for optical imaging of wafer positioning marks

Full-reference image quality assessment based on texture singular value decomposition

Full reference image quality assessment based on color appearance-based phase consistency

De-scattering method of underwater image based on imaging of specific polarization state

Pooling strategy for quality evaluation of full-reference model low illumination image

Related Author

LOU Peihuang

MENG Kai

ZHANG Hangying

YANG Jin

NIU Guangyue

FU Xiao

DUAN Fajie

LI Jiaxin

Related Institution

Key Laboratory of Aerospace Integrated Circuits and Microsystem， Ministry of Industry and Information Technology

National Key Laboratory of Microwave Photonics

College of Mechanical and Electrical Engineering， Nanjing University of Aeronautics and Astronautics

State Key Laboratory of Precision Measuring Technology & Instruments， Tianjin University

School of Artificial Intelligence， Anhui Polytechnic University

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰