Stable Third-Order Tensor Representation for Color Image Classification
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Multimodal biometrics using geometry preserving projections
Pattern Recognition
Image categorization: Graph edit distance+edge direction histogram
Pattern Recognition
A local Tchebichef moments-based robust image watermarking
Signal Processing
Gait Components and Their Application to Gender Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Effect of silhouette quality on hard problems in gait recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Wavelet-based color image compression: exploiting the contrast sensitivity function
IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
Orthogonal Laplacianfaces for Face Recognition
IEEE Transactions on Image Processing
No-reference image quality assessment in contourlet domain
Neurocomputing
Image quality assessment measure based on natural image statistics in the tetrolet domain
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
Adaptive image data hiding in edges using patched reference table and pair-wise embedding technique
Information Sciences: an International Journal
Local structure divergence index for image quality assessment
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Color fractal structure model for reduced-reference colorful image quality assessment
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
KIMEL: A kernel incremental metalearning algorithm
Signal Processing
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The human visual system (HVS) provides a suitable cue for image quality assessment (IQA). In this paper, we develop a novel reduced-reference (RR) IQA scheme by incorporating the merits from the contourlet transform, contrast sensitivity function (CSF), and Weber's law of just noticeable difference (JND). In this scheme, the contourlet transform is utilized to decompose images and then extract features to mimic the multichannel structure of HVS. CSF is applied to weight coefficients obtained by the contourlet transform to simulate the appearance of images to observers by taking into account many of the nonlinearities inherent in HVS. JND is finally introduced to produce a noticeable variation in sensory experience. Thorough empirical studies are carried out upon the Laboratory for Image and Video Engineering database against the subjective mean opinion score and demonstrate that the proposed framework has good consistency with subjective perception values and the objective assessment results can well reflect the visual quality of images.