Browse > Article
http://dx.doi.org/10.7840/kics.2013.38A.3.240

Effective Image Super-Resolution Algorithm Using Adaptive Weighted Interpolation and Discrete Wavelet Transform  

Lim, Jong Myeong (광운대학교 전자공학과 디지털미디어 연구실)
Yoo, Jisang (광운대학교 전자공학과 디지털미디어 연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.38A, no.3, 2013 , pp. 240-248 More about this Journal
Abstract
In this paper, we propose a super-resolution algorithm using an adaptive weighted interpolation(AWI) and discrete wavelet transform(DWT). In general, super-resolution algorithms for single-image, probability based operations have been used for searching high-frequency components. Consequently, the complexity of the algorithm is increased and it causes the increase of processing time. In the proposed algorithm, we first find high-frequency sub-bands by using DWT. Then we apply an AWI to the obtained high-frequency sub-bands to make them have the same size as the input image. Now, the interpolated high-frequency sub-bands and input image are properly combined and perform the inverse DWT. For the experiments, we use the down-sampled version of the original image($512{\times}512$) as a test image($256{\times}256$). Through experiment, we confirm the improved efficiency of the proposed algorithm comparing with interpolation algorithms and also save the processing time comparing with the probability based algorithms even with the similar performance.
Keywords
super-resolution; wavelet transform; adaptive weighted interpolation;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 S. Park, M. Park, and M. G. Kang, "Super-resolution image reconstruction: a technical overview," IEEE Signal Processing Mag., vol. 20, no. 3, pp. 21-36, May 2003.   DOI   ScienceOn
2 M. Irani and S. Peleg, "Improving resolution by image registration," CVGIP: Graphical Models Image Proc., vol. 53, no. 3, pp. 231-239, May 1991.
3 R. R. Schultz and R. L. Stevenson, "Extraction of high-resolution frames from video sequences," IEEE Trans. Image Process., vol. 5, no. 6, pp. 996-1011, June 1996.   DOI   ScienceOn
4 W. T. Freeman, T. R. Jonesm, and E. C. Pasztor, "Example-based super-resolution," IEEE Comput. Graph. Appl. (IEEE CG&A), vol. 22, no. 2, pp. 56-65, Mar. 2002
5 H. K. Kang and J. C. Cheon, "Texture mapping with bilinear interpolation," Korean Inst. Inform. Security (KIISC), vol. 26, no. 1, pp. 644-646, Apr. 1999.
6 Litakathunisa, C. N. R. Kumar, and V.K. Ananthashayana, "Super resolution reconstruction of compressed low resolution images using wavelet lifting schemes," in Proc. 2nd Int. Conf. Comput. Elect. Eng. (ICCEE 2009), pp. 629-633, Dec. 2009.
7 M. Belge, M. E. Kilmer, and E. L. Miller, "Wavelet domain image restoration with adaptive edge-preserving regularization," IEEE Trans. Image Process., vol. 9, no. 4, pp. 597-608, Apr. 2000.   DOI   ScienceOn
8 M. D. Robinson, C. A. Toth, J. Y. Lo, and S. Farsiu, "Efficient Fourier-wavelet super-resolution," IEEE Trans. Image Process., vol. 19, no. 10, pp. 2669-2681, Oct. 2010.   DOI   ScienceOn
9 L. Pu, W. Jin, and Y. Liu, "A post wavelet iterative filtering MAP super-resolution algorithm," in Proc. 4th Int. Conf. Fuzzy Syst. Knowledge Discovery (FSKD), pp. 226-230, Dec. 2007.
10 G. Anbarjafari and H. Demirel, "Image super resolution based on interpolation of wavelet domain high frequency sub-bands and the spatial domain input image," ETRI J., vol. 32, no. 3, pp. 390-394, June 2010.   과학기술학회마을   DOI
11 P. P. Gajjar and M. V. Joshi, "New learning based super-resolution: use of DWT and IGMRF prior," IEEE Trans. Image Process., vol. 19, no. 5, pp. 1201-1213, May 2010.   DOI   ScienceOn
12 Y. H. Baek, S. B. Oh, and S. R. Moon, "Super resolution based on reconstruction algorithm using wavelet basis," Inst. Electron. Eng. Korea Trans. Smart Process. Comput. (IEEK SPC), vol. 44, no 1, pp. 17-25, Jan. 2007.   과학기술학회마을
13 K. Kinebuchi, D. D. Muresan, and T. W. Parks, "Image interpolation using wavelet based hidden Markov trees",in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. (ICASSP), pp. 1957-1960, May 2001.
14 J. M. Lim and J. S. Yoo, "Super-resolution for single-image using discrete wavelet transform," Korean Soc. Broadcast Eng. (KSBE), pp. 139-142, Hanyang Univ. Korea, Nov. 2011.
15 S. Zhao, H. Han, and S. peng, "Wavelet-domain HMT-based image super resolution," in Proc. IEEE Int. Conf. Image Process. (IEEE ICIP), pp. 933-936, Beijing, China, Sep. 2003.
16 X. Li and M. T. Orchard, "New edge-directed interpolation," IEEE Trans. Image Process., vol. 10, no. 10, pp. 1521-1527, Oct. 2001.   DOI   ScienceOn
17 J. M. Lim and J. S. Yoo, "Depth map resolution enhancement based on adaptive weighted interpolation," Korean Soc. Broadcast Eng. (KSBE), pp. 26-28, Jeju Univ., Korea, July 2012.
18 Y. H. Seo, J. H. Kim, D. G. Kim, J. S. Yoo, and D. W. Kim, "An effective method to treat the boundary pixels for image compression with DWT," Korean Inst. Commun. Inform. Sci. (KICS), vol. 29, no. 6A, pp. 618-627, June 2002.   과학기술학회마을
19 Y. Yang and Z. Wang, "A new image super-resolution method in the wavelet domain," IEEE Int. Conf. Image Graphics (IEEE ICIG), pp. 163-167, Hefei, China, Aug. 2011.