Structural fidelity vs. naturalness - objective assessment of tone mapped images
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Optimal image restoration using HVS-based rate-distortion curves
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Exploring pixel-value differencing and base decomposition for low distortion data embedding
Applied Soft Computing
Computers & Mathematics with Applications
Fusion of mSSIM and SVM for reduced-reference facial image quality assessment
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Image quality assessment based on improved structural SIMilarity
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Visual saliency and distortion weighting based video quality assessment
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Assessment method of image super resolution reconstruction based on local similarity
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Fuzzy logic and temporal information applied to video quality assessment
Journal of Mobile Multimedia
SWVFS: a saliency weighted visual feature similarity metric for image quality assessment
Frontiers of Computer Science: Selected Publications from Chinese Universities
Saliency detection based on integrated features
Neurocomputing
Neural Network Guided Spatial Fault Resilience in Array Processors
Journal of Electronic Testing: Theory and Applications
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Many state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage structure: local quality/distortion measurement followed by pooling. While significant progress has been made in measuring local image quality/distortion, the pooling stage is often done in ad-hoc ways, lacking theoretical principles and reliable computational models. This paper aims to test the hypothesis that when viewing natural images, the optimal perceptual weights for pooling should be proportional to local information content, which can be estimated in units of bit using advanced statistical models of natural images. Our extensive studies based upon six publicly-available subject-rated image databases concluded with three useful findings. First, information content weighting leads to consistent improvement in the performance of IQA algorithms. Second, surprisingly, with information content weighting, even the widely criticized peak signal-to-noise-ratio can be converted to a competitive perceptual quality measure when compared with state-of-the-art algorithms. Third, the best overall performance is achieved by combining information content weighting with multiscale structural similarity measures.