Image Reconstruction with Usage of the F-Transform

Vlašánek, Pavel; Perfilieva, Irina

doi:10.1007/978-3-642-33018-6_52

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…In image processing, it has had successful applications in image compression and reduction, image fusion, edge detection and image reconstruction [14], [6], [15], [16], [17], [18]. The F-transform is a technique that places a continuous/discrete function in correspondence with a finite vector of its F-transform components.…”

Section: A F-transformmentioning

confidence: 99%

“…Thus, reconstruction uses pixels from a neighborhood of damaged ones and techniques of interpolation, extrapolation or approximation. Vlašánek In our previous work [17], we showed that the technique of F-transform is highly suitable for image reconstruction. We compared it to the technique of RBF -interpolation and showed its advantages in speed and quality.…”

Section: Introductionmentioning

confidence: 99%

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Interpolation techniques versus F-transform in application to image reconstruction

Vlašánek

Perfilieva

2014

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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Many interpolation techniques are available for image reconstruction, with differences in time complexity, memory complexity and quality. In this article, we compare the application of bilinear interpolation, nearest neighbor interpolation and the F-transform approximation technique to the problem of image reconstruction. Based on our results, Ftransform achieves the best results in terms of quality.

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Section: A F-transformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Interpolation techniques versus F-transform in application to image reconstruction

Vlašánek

Perfilieva

2014

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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“…This algorithm works well for photos [12,13,10,14] but not so sufficiently for low depth color images. The reason is in isotropic nature of the algorithm where different regions are mixed together in the inpainted area Ω.…”

Section: F-transformmentioning

confidence: 99%

Fuzzy image inpainting aimed to medical images

Vlašánek¹

2018

WSCG 2018 - Full Papers Proceedings

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This paper focuses on a reconstruction of low color depth images using fuzzy mathematics. For demonstration purposes, we chose medical images taken from magnetic resonance imaging (MRI) and computed tomography (CT). The proposed technique is based on idea of diffusion where pixels surrounding damaged region are used to determine the corrupted ones. As it is illustrated, the classical diffusion techniques are not so effective. In the paper, we describe the reason why and propose the solution in a form of the new algorithm. The algorithm is demonstrated and visually compared with another ones.

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“…In real life it may be a photography without inscribed time stamp, a fresco without cracks or a surface without stains for example. The idea of image reconstruction consists in interpolation [6] or approximation [7] of the missing intensity from the closest neighborhood. Because of that we have to distinguish between damaged and undamaged part.…”

Section: Image Reconstructionmentioning

confidence: 99%