Image Quality Assessment by Separately Evaluating Detail Losses and Additive Impairments

Li, Songnan; Zhang, Fan; Ma, Lin; Ngan, King Ngi

doi:10.1109/tmm.2011.2152382

Cited by 213 publications

(135 citation statements)

References 32 publications

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“…Among other measures, the fusion measure introduced in [28] also obtained good results, but was worse than rSIM2 (overall weighted). Measures trained on images from a given benchmark tend to perform worse on other benchmarks where some unknown distortion types are introduced, as for, e.g., [46] or [47]. For all examined IQA benchmark datasets, rSIM family of multimeasures showed superior performance: rSIM1 on TID2008; rSIM2 3 , rSIM4 3 , and rSIM4 2 on CSIQ; and rSIM2 3 , rSIM3 2 , and rSIM3 3 on LIVE.…”

Section: Discussionmentioning

confidence: 98%

A Regression-Based Family of Measures for Full-Reference Image Quality Assessment

Oszust

2016

Measurement Science Review

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The advances in the development of imaging devices resulted in the need of an automatic quality evaluation of displayed visual content in a way that is consistent with human visual perception. In this paper, an approach to full-reference image quality assessment (IQA) is proposed, in which several IQA measures, representing different approaches to modelling human visual perception, are efficiently combined in order to produce objective quality evaluation of examined images, which is highly correlated with evaluation provided by human subjects. In the paper, an optimisation problem of selection of several IQA measures for creating a regression-based IQA hybrid measure, or a multimeasure, is defined and solved using a genetic algorithm. Experimental evaluation on four largest IQA benchmarks reveals that the multimeasures obtained using the proposed approach outperform state-of-the-art full-reference IQA techniques, including other recently developed fusion approaches.

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Section: Discussionmentioning

confidence: 98%

A Regression-Based Family of Measures for Full-Reference Image Quality Assessment

Oszust

2016

Measurement Science Review

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“…Previous attempts in this direction appeared in [37], [38], where point-wise increments and decrements of the gradient magnitude were discriminated. In [39] detail losses and additive impairments were separated using a restored version of the test image as a watershed.…”

Section: B the Proposed Approachmentioning

confidence: 99%

“…For s = 1 pixel or slightly more, the frequency response of (1) well approximates the Contrast Sensitivity Function (CSF) of the HVS front end [39], [45], at nominal viewing distance [17]. The operator (1) summarizes the horizontal and vertical filters commonly used for gradient approximation [15] and is steerable, i.e., has the same frequency response for any pattern orientation [46].…”

Section: Detail Analysismentioning

confidence: 99%

A Detail-Based Method for Linear Full Reference Image Quality Prediction

Claudio

Jacovitti

2018

IEEE Trans. on Image Process.

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Abstract-In this paper, a novel Full Reference method is proposed for image quality assessment, using the combination of two separate metrics to measure the perceptually distinct impact of detail losses and of spurious details. To this purpose, the gradient of the impaired image is locally decomposed as a predicted version of the original gradient, plus a gradient residual. It is assumed that the detail attenuation identifies the detail loss, whereas the gradient residuals describe the spurious details. It turns out that the perceptual impact of detail losses is roughly linear with the loss of the positional Fisher information, while the perceptual impact of the spurious details is roughly proportional to a logarithmic measure of the signal to residual ratio. The affine combination of these two metrics forms a new index strongly correlated with the empirical Differential Mean Opinion Score (DMOS) for a significant class of image impairments, as verified for three independent popular databases. The method allowed alignment and merging of DMOS data coming from these different databases to a common DMOS scale by affine transformations. Unexpectedly, the DMOS scale setting is possible by the analysis of a single image affected by additive noise.

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“…The candidates for 2D metrics are SSIM [50], MS-SSIM [51], ADM [29], ADD-SSIM and ADD-GSIM [15]. The predictive performance of each metric is evaluated by four commonly used performance measures: the Pearson linear correlation coefficient (P LCC), the root mean squared error (RMSE), the Spearman rank-order correlation coefficient (SROCC) and Kendall rank-order correlation coefficient (KROCC).…”

Section: Performance Measurementioning

confidence: 99%

Quality assessment metric of stereo images considering cyclopean integration and visual saliency

Yang

Wang

et al. 2016

Information Sciences

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Citation: YANG, J. ... et al, 2016. Quality assessment metric of stereo images considering cyclopean integration and visual saliency.Information Sciences, 373, Additional Information:• This paper was accepted for publication in the journal Informa- AbstractIn recent years, there has been great progress in the wider use of threedimensional (3D) technologies. With increasing sources of 3D content, a useful tool is needed to evaluate the perceived quality of the 3D videos/images. This paper puts forward a framework to evaluate the quality of stereoscopic images contaminated by possible symmetric or asymmetric distortions. Human visual system (HVS)studies reveal that binocular combination models and visual saliency are the two key factors for the stereoscopic image quality assessment (SIQA) metric. Therefore inspired by such findings in HVS, this paper proposes a novel saliency map in SIQA metric for the cyclopean image called "cyclopean saliency", which avoids complex calculations and produces good results in detecting saliency regions. Moreover, experimental results show that our metric significantly outperforms conventional 2D quality metrics and yields higher correlations with human subjective judg- * Corresponding author ment than the state-of-art SIQA metrics. 3D saliency performance is also compared with "cyclopean saliency" in SIQA. It is noticed that the proposed metric is applicable to both symmetric and asymmetric distortions. It can thus be concluded that the proposed SIQA metric can provide an effective evaluation tool to assess stereoscopic image quality.

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Image Quality Assessment by Separately Evaluating Detail Losses and Additive Impairments

Cited by 213 publications

References 32 publications

A Regression-Based Family of Measures for Full-Reference Image Quality Assessment

A Regression-Based Family of Measures for Full-Reference Image Quality Assessment

A Detail-Based Method for Linear Full Reference Image Quality Prediction

Quality assessment metric of stereo images considering cyclopean integration and visual saliency

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