Yoshitaka Izumi
ABSTRACT
The purpose of this paper is two-fold. First, we develop a regularized and accelerated version of Ahmed's multi-channel blind deconvolution algorithm based on low-rank matrix recovery. Second, we apply the developed algorithm to motion-less super-resolution problem, which aims at recovering a high-resolution image from a set of differently blurred low-resolution images. We demonstrate performances of the proposed method by simulation studies and real-image experiments.
- J. V. Ouwerkerk, "Image super-resolution survey," Image and Vison Computing, vol. 24, pp. 1039--1052, 2006.Google Scholar
Cross Ref
- W. T. Freeman, T. R. Jones, and E. C. Pasztor, "Example-based super-resolution," IEEE Comput.Graph.Appl., vol. 22, no. 2, pp. 56--65, 2002.Google ScholarDigital Library
- S. C. Park, M. K. Park, and M. G. Kang, "Super-resolution image reconstruction: A technical overview," IEEE Signal Process.Mag., vol. 20, pp. 21--36, 2003.Google ScholarCross Ref
- M. Elad and A. Feuer, "Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images," IEEE Trans.Image Process., vol. 6, no. 12, pp. 1646--1658, 1997.Google ScholarDigital Library
- A. Ahmed, B. Recht, and J. Romberg, "Blind deconvolution using convex programming," IEEE Trans.Info.Theory, vol. 60, pp.1711--1732, 2014.Google ScholarDigital Library
- S. Kawakami and H. Kudo, "All-in-focus image generation using improved blind image deconvolution technique," Proc. of 2018 International Conference on Digital Medicine and Image Processing, pp.19--28, 2018.Google Scholar
- G. R. Ayers and J. C. Dainty, "Iterative blind deconvolution method and its applications," Opt.Lett., vol. 13, no. 7, pp. 547--549, 1988.Google ScholarCross Ref
- D. Kundur and D. Hatzinakos, "Blind image restoration via recursive filtering using deterministic constraints," Proc. of 1996 IEEE Int.Conf. on Acoust.Speech Signal Process., vol. 4, pp. 2283--2286, 1996.Google Scholar
- K. Toh and S. Yun, "An accelerated proximal gradient algorithm for nuclear norm regularized least squares problems," Pacific J.Opt., vol. 6, pp. 615--640, 2010.Google Scholar
- Q.Z. Huangpeng, X.G. Zeng, Q. Sun, and J. Fan, "Super-resolving blurry multiframe images through multiframe blind deblurring using ADMM," Multimedia Tools and Applications, pp.1--17, 2016.Google Scholar
- C. Lee and W. Hwang, "Mixture of gaussian blur kernel representation for blind image restoration," IEEE Trans.Comput.Imaging, vol. PP, no. 99, pp. 1--1, 2017.Google Scholar
- T.H. Ma, T.Z. Huang, X.L. Zhao, and Y. Lou, "Image deblurring with an inaccurate blur kernel using a group-based low-rank image prior," Information Sciences, vol. 408, pp. 213--233, 2017.Google ScholarCross Ref
- C. Dong, C. Change Loy, K. He, X. Tang, "Image super-resolution using deep convolutional networks," IEEE Trans.Patt.Anal.Machine Intell., vol.38, pp.295--307, 2015.Google ScholarDigital Library
Index Terms
- Motion-less super-resolution under blind condition using sparse optimization
Recommendations
Single image super-resolution via self-similarity and low-rank matrix recovery
We propose a novel single-image super resolution (SISR) approach using self-similarity of image and the low-rank matrix recovery (LRMR). The method performs multiple upsampling steps with relatively small magnification factors to recover a desired high ...
Context-aware single image super-resolution using sparse representation and cross-scale similarity
Methods for single image super-resolution (SR) are broadly divided into two categories: (i) edge-focused SR and (ii) example-based SR. Edge-focused methods are focused on producing sharp edges with minimal artifacts; however, these methods cannot ...
MR image super-resolution reconstruction using sparse representation, nonlocal similarity and sparse derivative prior
In magnetic resonance (MR) imaging, image spatial resolution is determined by various instrumental limitations and physical considerations. This paper presents a new algorithm for producing a high-resolution version of a low-resolution MR image. The ...
Comments