Journal ArticleDOI
Regularized Interative Image Interpolation and its application to Spatially Scalable Coding
Jeongho Shin,Junghoon Jung,Joonki Paik +2 more
- Vol. 44, Iss: 3, pp 1042-1047
TLDR
In this paper, a regularized iterative image interpolation algorithm was proposed to restore high frequency details in the original high resolution image, where the regularization approach was applied to the interpolation procedure.Abstract:
This paper presents a regularized iterative image interpolation algorithm, which can restore high frequency details in the original high resolution image In order to apply the regularization approach to the interpolation procedure, we first present a two-dimensional separable image degradation model for a low resolution imaging system According to the model, we propose a regularization based spatial image sequence interpolation algorithm and apply the proposed algorithm to a spatially scalable codingread more
Citations
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Journal ArticleDOI
Efficient implementation of image interpolation as an inverse problem
TL;DR: This paper presents three computationally efficient solutions for the image interpolation problem which are developed in a general framework and the performance of all the above-mentioned solutions is compared to traditional polynomial based interpolation techniques and to iterative interpolation as well.
Journal ArticleDOI
Regularized super-resolution reconstruction of images using wavelet fusion
TL;DR: The results indicate that the proposed regularized wavelet-based image super-resolution reconstruc- tion approach has succeeded in obtaining a high-resolution image from multiple degraded observations with a high peak SNR.
Journal ArticleDOI
Wavelet fusion: a tool to break the limits on lmmse image super-resolution
TL;DR: The proposed implementation has succeeded in obtaining a high-resolution image from multiple degraded observations with a high PSNR and the computation time of the suggested implementation is small when compared to traditional iterative image super-resolution algorithms.
Journal ArticleDOI
Blind multichannel reconstruction of high-resolution images using wavelet fusion
TL;DR: Results show that the suggested blind image reconstruction approach succeeds in estimating a high-resolution image from noisy blurred observations in the case of relatively coprime unknown blurring operators.
Proceedings ArticleDOI
Sectioned implementation of regularized image interpolation
TL;DR: In this article, a non-iterative regularized inverse solution to the image interpolation problem is proposed, which is based on segmentation of the image to be interpolated to overlapping blocks and interpolating each block separately.
References
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Book
Two-Dimensional Signal and Image Processing
TL;DR: This text covers the principles and applications of "multidimensional" and "image" digital signal processing and is suitable for Sr/grad level courses in image processing in EE departments.
Journal ArticleDOI
Image Restoration by the Method of Convex Projections: Part 1ߞTheory
D. C. Youla,H. Webb +1 more
TL;DR: In this article, a projection operator onto a closed convex set in Hilbert space is proposed for image restoration from partial data which permits any number of nonlinear constraints of a certain type to be subsumed automatically.
Journal ArticleDOI
A Bayesian approach to image expansion for improved definition
R.R. Schultz,Robert L. Stevenson +1 more
TL;DR: A method for nonlinear image expansion which preserves the discontinuities of the original image, producing an expanded image with improved definition is introduced.
Journal ArticleDOI
Constrained iterative restoration algorithms
TL;DR: It is shown that by predistorting the signal (and later removing this predistortion) it is possible to achieve spectral extrapolation, to broaden the class of signals for which these algorithms achieve convergence, and to improve their performance in the presence of broad-band noise.
Journal ArticleDOI
Iterative Image Restoration Algorithms
TL;DR: This tutorial paper discusses the use of successive-approximation-based iterative restoration algorithms for the removal of linear blurs and noise from images and regularization is introduced as a means for preventing the excessive noise magnification that is typically associated with ill-posed inverse problems such as the deblurring problem.