Journal ArticleDOI
Most apparent distortion: full-reference image quality assessment and the role of strategy
Eric C. Larson,Damon M. Chandler +1 more
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TLDR
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.Abstract:
The mainstream approach to image quality assessment has centered around accurately modeling the single most relevant strategy employed by the human visual system (HVS) when judging image quality (e.g., detecting visible differences, and extracting image structure/information). In this work, we suggest that a single strategy may not be sufficient; rather, we advocate that the HVS uses multiple strategies to determine image quality. For images containing near-threshold distortions, the image is most apparent, and thus the HVS attempts to look past the image and look for the distortions (a detection-based strategy). For images containing clearly visible distortions, the distortions are most apparent, and thus the HVS attempts to look past the distortion and look for the image's subject matter (an appearance-based strategy). Here, we present a quality assessment method [most apparent distortion (MAD)], which attempts to explicitly model these two separate strategies. Local luminance and contrast masking are used to estimate detection-based perceived distortion in high-quality images, whereas changes in the local statistics of spatial-frequency components are used to estimate appearance-based perceived distortion in low-quality images. We show that a combination of these two measures can perform well in predicting subjective ratings of image quality.read more
Citations
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Journal ArticleDOI
Retina inspired no-reference image quality assessment for blur and noise
Piyush Joshi,Surya Prakash +1 more
TL;DR: The proposed technique outperforms the latest no-training, no-reference (NR) based image quality assessment techniques and matches very well with human subjective opinions.
Journal ArticleDOI
Efficient Image Sharpness Assessment Based on Content Aware Total Variation
Khosro Bahrami,Alex C. Kot +1 more
TL;DR: The experimental results show that the proposed method is highly correlated with the human vision system and has better sharpness assessment results than the state-of-the-art techniques on the blurred subset images of LIVE, TID2008, CSIQ, and IVC databases.
Journal ArticleDOI
No-Reference Quality Assessment of Noise-Distorted Images Based on Frequency Mapping
TL;DR: Experimental results on three public databases show that the proposed FMIQA evaluates the noise-distorted image in consistency with subjective assessment and can obtain better performance in image quality prediction than other existing related methods.
Journal ArticleDOI
Lossy Image Compression with Conditional Diffusion Models
Ruihan Yang,Stephan Mandt +1 more
TL;DR: This paper outlines an end-to-end optimized framework based on a conditional diffusion model for image compression that out-performs one of the best-performing conventional image codecs and one neural codec on two compression benchmarks, where the focus on rate-perception tradeoffs.
Journal ArticleDOI
ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction
TL;DR: In this paper, a generalized Gaussian distribution (GGD) is used to model band-pass responses, while entropy variations between reference and distorted videos under the GGD model are used to capture video quality variations arising from frame rate changes.
References
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Journal ArticleDOI
Image quality assessment: from error visibility to structural similarity
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Proceedings ArticleDOI
Multiscale structural similarity for image quality assessment
TL;DR: This paper proposes a multiscale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions, and develops an image synthesis method to calibrate the parameters that define the relative importance of different scales.
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Sparse Coding with an Overcomplete Basis Set: A Strategy Employed by V1 ?
TL;DR: These deviations from linearity provide a potential explanation for the weak forms of non-linearity observed in the response properties of cortical simple cells, and they further make predictions about the expected interactions among units in response to naturalistic stimuli.
Journal ArticleDOI
Efficient tests for normality, homoscedasticity and serial independence of regression residuals
Carlos M. Jarque,Anil K. Bera +1 more
TL;DR: In this paper, the Lagrange multiplier procedure is used to derive efficient joint tests for residual normality, homoscedasticity and serial independence, which are simple to compute and asymptotically distributed as χ2.
Journal ArticleDOI
Image information and visual quality
Hamid R. Sheikh,Alan C. Bovik +1 more
TL;DR: An image information measure is proposed that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image and combined these two quantities form a visual information fidelity measure for image QA.