Framework for Applying Full Reference Digital Image Quality Measures to Printed Images
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Iterative PSF estimation and its application to shift invariant and variant blur reduction
EURASIP Journal on Advances in Signal Processing
A no-reference perceptual blur metric using histogram of gradient profile sharpness
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Towards video quality metrics based on colour fractal geometry
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
Degradation based blind image quality evaluation
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Self-similarity measure for assessment of image visual quality
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
No reference image quality assessment using fuzzy relational classifier
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I
The role of attractiveness in web image search
MM '11 Proceedings of the 19th ACM international conference on Multimedia
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
NoRM: No-Reference Image Quality Metric for Realistic Image Synthesis
Computer Graphics Forum
Correction, stitching and blur estimation of micro-graphs obtained at high speed
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
Fusion of mSSIM and SVM for reduced-reference facial image quality assessment
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
A two-stage quality measure for mobile phone captured 2D barcode images
Pattern Recognition
Wave atoms based compression method for fingerprint images
Pattern Recognition
No-reference blur image quality measure based on multiplicative multiresolution decomposition
Journal of Visual Communication and Image Representation
Fast image enhancement in compressed wavelet domain
Signal Processing
Where should I stand? Learning based human position recommendation for mobile photographing
Multimedia Tools and Applications
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Measurement of image or video quality is crucial for many image-processing algorithms, such as acquisition, compression, restoration, enhancement, and reproduction. Traditionally, image quality assessment (QA) algorithms interpret image quality as similarity with a "reference" or "perfect" image. The obvious limitation of this approach is that the reference image or video may not be available to the QA algorithm. The field of blind, or no-reference, QA, in which image quality is predicted without the reference image or video, has been largely unexplored, with algorithms focussing mostly on measuring the blocking artifacts. Emerging image and video compression technologies can avoid the dreaded blocking artifact by using various mechanisms, but they introduce other types of distortions, specifically blurring and ringing. In this paper, we propose to use natural scene statistics (NSS) to blindly measure the quality of images compressed by JPEG2000 (or any other wavelet based) image coder. We claim that natural scenes contain nonlinear dependencies that are disturbed by the compression process, and that this disturbance can be quantified and related to human perceptions of quality. We train and test our algorithm with data from human subjects, and show that reasonably comprehensive NSS models can help us in making blind, but accurate, predictions of quality. Our algorithm performs close to the limit imposed on useful prediction by the variability between human subjects.