Image blur estimation using gradient field analysis

Asatryan, David

doi:10.18287/2412-6179-2017-41-6-957-962

Cited by 13 publications

(7 citation statements)

References 4 publications

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“…Such metrics make possible to evaluate the quality based on the image only without the reference. Part of the metrics is developed to assess the single factor affecting the quality, for example, the blurriness level [17]. Other ones claim to be universal.…”

Section: Resultsmentioning

confidence: 99%

The regression model for the procedure of correction of photos damaged by backlighting

Goncharova¹,

Safonov

Romanov³

2019

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

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In the paper, we propose an approach for selection a correction parameter for images damaged by backlighting. We consider the photos containing underexposed areas due to backlit conditions. Such areas are dark and have poorly discernible details. The correction parameter controls the level of amplification of local contrast in shadow tones. Besides, the correction parameter can be considered as a quality estimation factor for such photos. For an automatic selection of the correction parameter, we apply regression by supervised machine learning. We propose new features calculated from the co-occurrence matrix for the training of the regression model. We compare the performance of the following techniques: the least square method, support vector machine, random forest, CART, random forest, two shallow neural networks as well as blending and staking of several models. We apply two-stage approach for the collection of a big dataset for training: initial model is trained on a manually labeled dataset containing about two hundred of photos, after that we use the initial model for searching for photos damaged by backlit in social networks having public API. Such approach allowed to collect about 1000 photos in conjunction with their preliminary quality assessments that were corrected by experts if it was necessary. In addition, we investigate an application of several well-known blind quality metrics for the estimation of photos affected by backlit.

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Section: Resultsmentioning

confidence: 99%

The regression model for the procedure of correction of photos damaged by backlighting

Goncharova¹,

Safonov

Romanov³

2019

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

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“…Our recent studies have shown that the value of the statistical estimate of shape parameter η of Weibull distribution can be used as a blur measure. In [15], on simulated blur data of various images, it is shown that the value of the parameter estimate increases monotonically as the degree of blurring increases. For example, Figure 4 shows an image and its blurred patterns, with the corresponding values of parameter η.…”

Section: Applicationsmentioning

confidence: 99%

“…It is also shown in [15] that in general the parameter η can be interpreted as a measure for image structuredness.…”

Section: Applicationsmentioning

confidence: 99%

Gradient-based technique for image structural analysis and applications

Asatryan¹

2019

Computer Optics

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This paper is devoted to application of gradients field characteristics in selected problems of image intellectual analysis and processing. To analyse the properties and structure of an image several approaches and models based on the use of the gradients field characteristics, are proposed. In this paper, models based on Weibull distribution are considered, an image dominant direction estimation algorithm using the parameters of scattering ellipse of gradients field components is proposed, and a similarity measure of two images with arbitrary dimensions and orientation is proposed. Some examples of applications of these models for estimation of blur and structuredness of an image, for the quality assessment of resizing and rotating algorithms, as well as for detection of a specified object on the image delivered by an unmanned aerial vehicle, are given.

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“…Such metrics make possible to evaluate the quality based on the image only without the reference. Part of the metrics is designed to assess one factor affecting the quality, for example, the blurriness level [14].…”

Section: Analysis Of the Use Of No-reference Quality Metrics For Micro-ct Imagesmentioning

confidence: 99%

Selection in a 3D microtomographic image the region with the highest quality

Kornilov

Safonov

Goncharova³

et al. 2019

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

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We present an algorithm for processing of X-ray microtomographic (micro-CT) images that allows automatic selection of a sub-volume having the best visual quality for further mathematical simulation, for example, flow simulation. Frequently, an investigated sample occupies only a part of a volumetric image or the sample can be into a holder; a part of the image can be cropped. For each 2D slice across the Z-axis of an image, the proposed method locates a region corresponding to the sample. We explored applications of several existing blind quality measures for an estimation of the visual quality of a micro-CT image slice. Some of these metrics can be applied to ranking the image regions according to their quality. Our method searches for a cubic area located inside regions belonging to the sample and providing the maximal sum of the quality measures of slices crossing the cube across the Z-axis. The proposed technique was tested on synthetic and real micro-CT images of rocks.

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Image blur estimation using gradient field analysis

Cited by 13 publications

References 4 publications

The regression model for the procedure of correction of photos damaged by backlighting

The regression model for the procedure of correction of photos damaged by backlighting

Gradient-based technique for image structural analysis and applications

Selection in a 3D microtomographic image the region with the highest quality

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