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Journal ArticleDOI

Most apparent distortion: full-reference image quality assessment and the role of strategy

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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.

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Citations
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Journal ArticleDOI

No Reference Image Quality Assessment based on Multi-Expert Convolutional Neural Networks

TL;DR: A novel NR IQA algorithm based on multi-expert convolutional neural networks (CNNs), which consists of distortion type classification, CNN based IQA algorithms and fusion algorithm is developed.
Book ChapterDOI

Analysis of HVS-Metrics' Properties Using Color Image Database TID2013

TL;DR: This paper determines and analyzes image statistics such as mean and standard deviation for several state of the art quality metrics on classes of images with multiple or particular types of distortions for HVS-metrics from another practically important viewpoint.
Journal ArticleDOI

Blind Image Quality Assessment via Vector Regression and Object Oriented Pooling

TL;DR: This paper presents an effective method based on vector regression and object oriented pooling for blind image quality assessment that achieves state-of-the-art performance and shows a great generalization ability.
Journal ArticleDOI

Fine-Grained Quality Assessment for Compressed Images

TL;DR: A large-scale image database which can be used for fine-grained quality assessment of compressed images and sixteen well-known IQA algorithms are evaluated and analyzed on the proposed database.
Journal ArticleDOI

Algorithm for JPEG artifact reduction via local edge regeneration

TL;DR: The proposed algorithm addresses all three types of artifacts which are prevalent in JPEG images: blocking, and for edges blurring, and aliasing, and enhances the quality of the image via two stages.
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.
Journal ArticleDOI

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

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

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.
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