Blurring image quality assessment method based on histogram of gradient

Authors:
Sangwoo Ahn;Jongjoo Park;Jongwha Chong
Affiliations:
HanyangUniversity, Seoul, South Korea;Hanyang University, Seoul, South Korea;Hanyang University, Seoul, South Korea
Venue:
Proceedings of the 19th Brazilian symposium on Multimedia and the web
Year:
2013

Citing 8
Cited 0

Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

Communications of the ACM
Histograms of Oriented Gradients for Human Detection

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Removing camera shake from a single photograph

ACM SIGGRAPH 2006 Papers
Study of subjective and objective quality assessment of video

IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity

IEEE Transactions on Image Processing
Image information and visual quality

IEEE Transactions on Image Processing
VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images

IEEE Transactions on Image Processing
Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

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.