ABSTRACT
In this paper we propose a blurring image quality assessment (IQA) based on histogram of oriented gradients (HOG). The image quality can be determined by the slope value of the HOG of the target image. The representative line of HOG is approximated by a random sample consensus set (RANSAC). Simulation results performed on the LIVE image quality assessment database show that the proposed method aligns better with how the human visual system perceives image quality than several state-of-the-art IQAs.
- Z. Wang and A. C. Bovik, Modern Image Quality Assessment, New York Morgan and Claypool Publishing Company, 2006.Google ScholarCross Ref
- Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simonecelli, "Image quality assessment: From error visibility to structural similarity," IEEE Transactions on Image Processing, vol.13, no.4, pp.600--612, Apr. 2004. Google ScholarDigital Library
- A. K. Moorthy and A. C. Bovik, "Blind Image Quality Assessment: From NaturalScene Statistics to Perceptual Quality," IEEE Transactions on Image Processing, vol.20, no.12, pp.3350--3364, Dec. 2011. Google ScholarDigital Library
- } R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis and W. T. Freeman, "Removing camera shake from a single photograph," ACM Transaction on Graphics, vol.25, no.3, pp.787--794, Jul. 2006. DOI = http://dl.acm.org/citation.cfm?doid=1179352.1141956 Google ScholarDigital Library
- N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 886--893, June. 2005. Google ScholarDigital Library
- M. Fischler and R. Bolles, "Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography," Communications of the ACM, vol.24, no.6, pp.381--395, Jun. 1981. DOI = http://dl.acm.org/citation.cfm?doid=358669.358692 Google ScholarDigital Library
- K. Seshadrinathan, R. Soundararajan, A. C. Bovik and L. K. Cormack, "Study of Subjective and Objective Quality Assessment of Video," IEEE Transactions on Image Processing, vol.19, no.6, pp.1427--1441, Jun. 2010. Google ScholarDigital Library
- H. R. Sheikh, Z. Wang, L. Cormack and A. C. Bovik, "LIVE Image Quality Assessment Database Release 2", http://live.ece.utexas.edu/research/quality.Google Scholar
- D. M. Chandler and S. S. Hemami, "VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images," IEEE Transactions on Image Processing, vol.16, no.9, pp.2284--2298, Sep. 2007. Google ScholarDigital Library
- H. R. Sheikh and A. C. Bovik, "Image information and visual quality," IEEE Transactions on Image Processing, vol.15, no.2, pp.430--444, Jan. 2006. Google ScholarDigital Library
- A. K. Moorthy and A. C. Bovik, "A Two-Step Framework for Constructing Blind Image Quality Indices," IEEE Signal Processing Letters, vol.17, no.5, pp.513--516, May. 2010.Google ScholarCross Ref
Index Terms
- Blurring image quality assessment method based on histogram of gradient
Recommendations
No-reference image quality assessment based on gradient histogram response
A NR image quality assessment based on gradient histogram response (GHR) is proposed.A test image is preprocessed to produce a noise image object and a blur image object.GHR is the gradient histogram variation of an image object under a local ...
A Gradient Weighted Structural Similarity Metric for Image Quality Assessment
ICECC '12: Proceedings of the 2012 International Conference on Electronics, Communications and ControlThe assessment of image quality is very important for numerous image processing applications, where the goal of image quality assessment (IQA) algorithms is to automatically assess the quality of images in a manner that is consistent with human visual ...
Gradient information-based image quality metric
In this paper, we propose a new image quality metric using the gradient information. When an image is degraded, the difference exists between the reference and distorted images. This difference is an important factor in image quality assessment. To ...
Comments