A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The visible differences predictor: an algorithm for the assessment of image fidelity
Digital images and human vision
Human Carrying Status in Visual Surveillance
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Knowledge and Information Systems
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image quality assessment based on a degradation model
IEEE Transactions on Image Processing
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
A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
IEEE Transactions on Image Processing
A distortion measure for blocking artifacts in images based on human visual sensitivity
IEEE Transactions on Image Processing
A Convolutional Neural Network Approach for Objective Video Quality Assessment
IEEE Transactions on Neural Networks
Feature correlation evaluation approach for iris feature quality measure
Signal Processing
No-reference image quality assessment in contourlet domain
Neurocomputing
A blind watermarking scheme using new nontensor product wavelet filter banks
IEEE Transactions on Image Processing
Content-adaptive reliable robust lossless data embedding
Neurocomputing
Transforming Japanese archives into accessible digital books
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
Contour extraction of gait recognition based on improved GVF Snake model
Computers and Electrical Engineering
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
An image quality assessment algorithm based on feature selection
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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Reduced-reference (RR) image quality assessment (IQA) has been recognized as an effective and efficient way to predict the visual quality of distorted images. The current standard is the wavelet-domain natural image statistics model (WNISM), which applies the Kullback-Leibler divergence between the marginal distributions of wavelet coefficients of the reference and distorted images to measure the image distortion. However, WNISM fails to consider the statistical correlations of wavelet coefficients in different subbands and the visual response characteristics of the mammalian cortical simple cells. In addition, wavelet transforms are optimal greedy approximations to extract singularity structures, so they fail to explicitly extract the image geometric information, e.g., lines and curves. Finally, wavelet coefficients are dense for smooth image edge contours. In this paper, to target the aforementioned problems in IQA, we develop a novel framework for IQA to mimic the human visual system (HVS) by incorporating the merits from multiscale geometric analysis (MGA), contrast sensitivity function (CSF), and the Weber's law of just noticeable difference (JND). In the proposed framework, MGA is utilized to decompose images and then extract features to mimic the multichannel structure of HVS. Additionally, MGA offers a series of transforms including wavelet, curvelet, bandelet, contourlet, wavelet-based contourlet transform (WBCT), and hybrid wavelets and directional filter banks (HWD), and different transforms capture different types of image geometric information. CSF is applied to weight coefficients obtained by MGA 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 LIVE database against subjective mean opinion score (MOS) and demonstrate that 1) the proposed framework has good consistency with subjective perception values and the objective assessment results can well reflect the visual quality of images, 2) different transforms in MGA under the new framework perform better than the standard WNISM and some of them even perform better than the standard full-reference IQA model, i.e., the mean structural similarity index, and 3) HWD performs best among all transforms in MGA under the framework.