Analysis of exemplar based inpainting techniques for error concealment

Yastrebov, Victor A.; Veselov, Anton; Filippov, Boris

doi:10.1109/red.2014.7016715

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Digital image inpainting is the process of reconstructing completely lost or deteriorated parts of images or removing unwanted elements in an undetectable manner. Smart digital inpainting techniques have broad applications in computer vision and image processing, such as the restoration of valuable paintings or damaged photos for conservation purposes [1], text or object removal from photographs for special effects [2], error concealment in videos [3], magnification and super-resolution [4] etc. The key task in inpainting is to build the relationship between the residual parts and the missing ones.…”

Section: Introductionmentioning

confidence: 99%

An effective LRTC model integrated with total α ‐order variation and boundary adjustment for multichannel visual data inpainting

Yang

Xue

et al. 2022

IET Image Processing

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Restoring damaged multichannel visual data with high loss ratio is quite a challenging task. To address this problem, an effective LRTC (low‐rank tensor completion) model integrated with total α‐order variation (TVα) in the fractional bounded variation space BVα is proposed to perform superior fractional‐in‐space regularization. Based on using LR constraint to restore global patterns, TVα regularization is integrated to exploit nonlocally‐correlated information on each channel to infer the lost data and simultaneously effectively deal with complex details due to the powerful fractional calculus. Then, a nonlocal fractional regularization strategy for multi‐dimensional data and an effective numerical optimization method are creatively designed to solve this problem. Two novel fractional derivative matrix approximations are derived and applied to the first two unfolding modes of the tensor respectively to conveniently solve the fractional regularization subproblem by using an element‐wise shrinkage‐thresholding operation. In addition, boundary extension and adjustment strategy are designed for the unfolded matrices to alleviate the influence of inaccurate boundary conditions in fractional derivative computations. Experiments are conducted to illustrate its performance and efficiency for YUV video, RGB and HSI restoration, especially its ability to effectively recover complex structures and the details of multi‐component visual data with relatively high missing rate.

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Section: Introductionmentioning

confidence: 99%

An effective LRTC model integrated with total α ‐order variation and boundary adjustment for multichannel visual data inpainting

Yang

Xue

et al. 2022

IET Image Processing

View full text Add to dashboard Cite

show abstract

“…in an undetectable manner. Smart digital inpainting techniques have broad applications in computer vision and image processing, such as the restoration of valuable paintings or damaged photos for conservation purposes [1], text or object removal from photographs for special effects [2], disocclusion in computer vision [3, 4], error concealment in videos [5, 6], and magnification and super‐resolution [7, 8].…”

Section: Introductionmentioning

confidence: 99%

Fractional‐order tensor regularisation for image inpainting

Yang

Guo

2017

IET Image Processing

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Quality Management in Development and Practical Use of Software Systems

Yastrebov

Korshunov

Varzhapetyan

2018

Voprosy radioèlektroniki

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In the article topical issues of quality assurance of software complexes (PCs) are considered. The special role in the organization of the processes of PC development of information services is emphasized, the implementation of which is carried out with the help of appropriate information resources, including a set of knowledge, data, artificial intelligence systems, analysis and information processing systems that serve as the basis for PC production. It is shown that the successful implementation of design work should be systematically implemented on the basis of appropriate information support, which is based on a variety of information products. Particular attention is paid to the analysis of risks arising during the development and operation of the PC. The novelty of the conducted research consists in the complex consideration of the tasks of increasing the reliability of the PC and minimizing the risks on the basis of using the methods of automated testing of software products. It is shown that the application of PC testing methods provides an increase in the reliability of design solutions and the effectiveness of practical implementation of developments.

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Analysis of exemplar based inpainting techniques for error concealment

Cited by 3 publications

References 7 publications

An effective LRTC model integrated with total α ‐order variation and boundary adjustment for multichannel visual data inpainting

An effective LRTC model integrated with total α ‐order variation and boundary adjustment for multichannel visual data inpainting

Fractional‐order tensor regularisation for image inpainting

Quality Management in Development and Practical Use of Software Systems

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