Most apparent distortion: full-reference image quality assessment and the role of strategy
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Summary
A quality assessment method [most apparent distortion (MAD)], which attempts to explicitly model these two separate strategies, local luminance and contrast masking and changes in the local statistics of spatial-frequency components are used to estimate appearance-based perceived distortion in low-quality images.
- Type
- article
- Published
- 2010-01-01
- Cited by
- 2,056
- References
- 66
- OpenAlex
- https://openalex.org/W2171349048
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9341989
Keywords
Artificial intelligence, Distortion (music), Image quality, Computer vision, Luminance
References
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- Most apparent distortion: a dual strategy for full-reference image quality assessment
- Visual quality assessment using a contrast gain control model
- Efficient tests for normality, homoscedasticity and serial independence of regression residuals
- Suprathreshold image compression based on contrast allocation and global precedence
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- Full-reference image quality assessment by combining global and local distortion measures
- A Comparison of Image Processing Techniques for Bird Detection
- Capturing structural distortions in digital images and videos
- Saliency-Aware Video Compression
- Blind Image Blur Assessment Using Singular Value Similarity and Blur Comparisons
- Perceptual Quality Assessment of Screen Content Images
- Tchebichef moment based restoration of Gaussian blurred images.
- dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs
- Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images
- Bayesian Dictionary Learning for Single and Coupled Feature Spaces
- Visual attention pooling and understanding the structural similarity index in multi-scale analysis
- Image focus measure based on polynomial coefficients and spectral radius
- JPEG 2000 Quality Scalability in an IP Networking Scenario
- Still image/video frame lossy compression providing a desired visual quality
- Evaluating and Improving Image Quality of Tiled Displays
- Feature selection for low bit rate mobile augmented reality applications
- Methods for Objective and Subjective Video Quality Assessment and for Speech Enhancement
- On the optimisation of nonlinear mapping functions towards high correlation of full-reference image quality metrics and their combinations with subjective evaluations
- A blur estimation and detection method for out-of-focus images
- A harmonic means pooling strategy for structural similarity index measurement in image quality assessment
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