Two-frames image superresolution based on the aggregate divergence matrix

Peleshko, Dmytro; Rak, Taras; Peleshko, Marta; Izonin, Ivan; Batyuk, Danylo

doi:10.1109/dsmp.2016.7583548

Cited by 18 publications

(8 citation statements)

References 9 publications

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“…Since the input in this case there are two images І 1 and І 2 , there are at least three solutions of the problem oversamp ling. The first two are similar to [1,2] consists in the build ing enhanced images added to the original matrix and І 1 or І 2 vector с i + y i position in line (or colu mn). Here с ithe function of intensity of the input image (i.e., the original, not normalized by (2) and (3) of significance).…”

Section: Algorithmic Implementation Of Methodsmentioning

confidence: 99%

“…The first two are similar to [1,2] consists in the build ing enhanced images added to the original matrix and І 1 or І 2 vector с i + y i position in line (or colu mn). Here с ithe function of intensity of the input image (i.e., the original, not normalized by (2) and (3) of significance). A third solution is the synthesis of matrix rows and colu mns, enhanced by the expression: SR increase procedure similar to the procedure described in [1,2], consists of two consecutive parts, which oversampling image carried in the vertical and horizontal d irections, respectively.…”

Section: Algorithmic Implementation Of Methodsmentioning

confidence: 99%

“…Aggregate divergence matrix i  , that is the basis of the superresolution method, in the case of two input images, is constructed as follows [2]:…”

Section: Divergence Matrix Constructionmentioning

confidence: 99%

“…-Ku lchynska appropriate plural [7], Otiai [8], Sorensen [9] Braun-Blanquet [10] Shy mkevycha-Simpson [11,12], Jacquard [13]. In the event of I (2) and reference the twice en larged image   2 m I these plurals as described in [13] at the fixed value of the coefficient k are written as follows: 2 2 2 2 ет ет 2 2 2 2 0,0 ет 0, ет 2 2 2 2 2 2 ет ет ет 2 2 2 2 ет ет 2 2 2 2 0,1 ет 0, 1 ет 2 2 2 2 2 2 ет ет ет 2 2 2 22 ет ет 2 2 2 2 1, 1 ет 0, ет 22 ет 2 , ; , ; 2 , ; , ; 2 2 , ; , I I I I K I I K I I I I I I II I I I I K I I K I...…”

Section: Automatically Determining T He Coefficient Of Crossover mentioning

confidence: 99%

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Image Superresolution via Divergence Matrix and Automatic Detection of Crossover

Peleshko¹,

Rak²,

Izonin³

2016

IJISA

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The paper describes the image superresolution method with aggregate divergence matrix and automatic detection of crossover. Formulation of the problem, building extreme optimization task and its solution for solving the automation determination of the crossover coefficient is presented. Different ways for building oversampling images algorith ms based on the proposed method are shows. Based on practical experiments shows the effectiveness of the procedure of automatically the determination of the crossover coefficient. Experimentally established the effectiveness of the procedures oversampling images at high zoo m resolution by the developed method.

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Section: Algorithmic Implementation Of Methodsmentioning

confidence: 99%

Section: Algorithmic Implementation Of Methodsmentioning

confidence: 99%

“…Aggregate divergence matrix i  , that is the basis of the superresolution method, in the case of two input images, is constructed as follows [2]:…”

Section: Divergence Matrix Constructionmentioning

confidence: 99%

Section: Automatically Determining T He Coefficient Of Crossover mentioning

confidence: 99%

See 2 more Smart Citations

Image Superresolution via Divergence Matrix and Automatic Detection of Crossover

Peleshko¹,

Rak²,

Izonin³

2016

IJISA

Self Cite

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“…The most common indicator to evaluate the image quality of an optical system is the resolution, i.e. the abi lity to separately observe the images of two objects located very close to each other [2].…”

Section: Introductionmentioning

confidence: 99%

Optical quality of the image and methods of its determination

Havrysh¹,

Tymchenko²,

Logoida³

et al. 2018

Print. Publish.

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The main objective of the assessment of the production process is obtaining objective information on the functioning of equipment and technology for the identification of intensification reserves of production to increase its efficiency and quality, increase production, increase productivity, reduce all kinds of material and labour costs. Quality is a set of characteristics of the object concerning its ability to meet established and anticipated needs. The article deals with the evaluation criteria such as quality image resolution, i.e. the ability to separately observe the image of two very close objects.

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A Study on Image Comparison Metrics for Atmospheric Scattering Phenomenon Rendering

Gałaj

Wojciechowski

2018

Computer Vision and Graphics

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Two-frames image superresolution based on the aggregate divergence matrix

Cited by 18 publications

References 9 publications

Image Superresolution via Divergence Matrix and Automatic Detection of Crossover

Image Superresolution via Divergence Matrix and Automatic Detection of Crossover

Optical quality of the image and methods of its determination

A Study on Image Comparison Metrics for Atmospheric Scattering Phenomenon Rendering

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