Wavelet-based contourlet in quality evaluation of digital images

Authors:
Xinbo Gao;Wen Lu;Xuelong Li;Dacheng Tao
Affiliations:
School of Electronic Engineering, Xidian University, Xi'an 710071, China;School of Electronic Engineering, Xidian University, Xi'an 710071, China;School of Computer Science and Information Systems, Birkbeck, University of London, London WC1E 7HX, UK;Biometrics Research Centre, Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Venue:
Neurocomputing
Year:
2008

Citing 10
Cited 4

Human Carrying Status in Visual Surveillance

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Supervised tensor learning

Knowledge and Information Systems
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Reduced Reference Image Quality Assessment Based on Contourlet Domain and Natural Image Statistics

ICIG '09 Proceedings of the 2009 Fifth International Conference on Image and Graphics
A filter bank for the directional decomposition of images: theoryand design

IEEE Transactions on Signal Processing
Wavelet-based color image compression: exploiting the contrast sensitivity function

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

IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation

IEEE Transactions on Image Processing
An information fidelity criterion for image quality assessment using natural scene statistics

IEEE Transactions on Image Processing
Quality-aware images

IEEE Transactions on Image Processing

Image quality assessment based on multiscale geometric analysis

IEEE Transactions on Image Processing
Rotation invariant iris feature extraction using Gaussian Markov random fields with non-separable wavelet

Neurocomputing
Video-based non-uniform object motion blur estimation and deblurring

Neurocomputing
Wave atoms based compression method for fingerprint images

Pattern Recognition

Quantified Score

Hi-index	0.01

Visualization

Abstract

Feature extraction is probably the most important stage in image quality evaluation-effective features can well reflect the quality of digital images and vice versa. As a non-redundant sparse representation, contourlet transform can effectively reflect visual characteristics of images, and it can be employed to perceptually capture the difference between images. Motivated by this, this paper first proposes an objective reduced-reference image quality evaluation metric based on contourlet transform. Experiments demonstrate that this new objective metric achieves consistent image quality evaluation results with what gained by subjective evaluation.