Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality
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- Type
- article
- Published
- 2011-12-01
- Cited by
- 1,763
- References
- 69
- OpenAlex
- https://openalex.org/W2129644086
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:497740
Keywords
Distortion (music), Image quality, Scene statistics, Artificial intelligence, Computer science
References
- Natural image statistics and divisive normalization: Modeling nonlinearity and adaptation in cortical neurons
- What's wrong with mean-squared error?
- Estimation of shape parameter for generalized Gaussian distributions in subband decompositions of video
- Fast structural similarity index algorithm
- No-reference image blur assessment using multiscale gradient
- Perceptual image distortion
- No reference image quality assessment for JPEG2000 based on spatial features
- The Essential Guide to Video Processing
- Image information and visual quality
- Embedded image coding using zerotrees of wavelet coefficients
- Perceptually significant spatial pooling techniques for image quality assessment
- Modern Image Quality Assessment
- A single-ended blockiness measure for JPEG-coded images
- No-reference visually significant blocking artifact metric for natural scene images
- Handbook of Parametric and Nonparametric Statistical Procedures
- Statistics of natural image distortions
- Sparse representation for blind image quality assessment
- No-reference perceptual quality assessment of JPEG compressed images
- No-reference quality assessment for JPEG2000 compressed images
- Shiftable multiscale transforms
Cited by
- dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs
- Medical Image Quality Assessment Using CSO Based Deep Neural Network
- Analysis of Blind Image Quality Index
- Multiuser Detection in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Systems by Blind Signal Separation Techniques
- Nonlinear Adaptive Diffusion Models for Image Denoising
- Automated content and quality assessment of full-motion-video for the generation of meta data
- No-reference image quality assessment algorithms: A survey
- From Full-Reference to No-Reference in Quality Assessment of Printed Images
- No-reference Video Quality Assessment and Applications
- No-reference image quality assessment using Prewitt magnitude based on convolutional neural networks
- Digital Fingerprint Quality Assessment
- Automatic Prediction of Perceptual Image and Video Quality
- Rule-based combination of video quality metrics
- Video authentication in digital forensic
- A no reference image quality measure using a distance doubling variance
- Gradient-based no-reference image blur assessment using extreme learning machine
- No-reference image quality assessment based on phase congruency and spectral entropies
- Multiscale fusion of depth estimations for haze removal
- No-Reference Image Sharpness Assessment in Autoregressive Parameter Space
- Revealing the dark side of a subjective study: Learnings from noise and sharpness ratings
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