Natural Image Super Resolution through Modified Adaptive Bilinear Interpolation Combined with Contra Harmonic Mean and Adaptive Median Filter

Full Text (PDF, 778KB), PP.1-8

Views: 0 Downloads: 0


Suresha D 1,* Prakash H N 2

1. Visvesvaraya Technological University, Belagavi, 590018, India

2. Department of Computer Science and Engineering, Rajeev Institute of Technology, Hassan, 573201, India

* Corresponding author.


Received: 2 Nov. 2015 / Revised: 27 Nov. 2015 / Accepted: 5 Jan. 2016 / Published: 8 Feb. 2016

Index Terms

Super resolution, nearest neighbor, bilinear, bicubic, modified adaptive bilinear interpolation, contra harmonic mean, adaptive median filter


Super resolution is a technique to enhance the scale of image in digital image processing. The single low resolution and multiple low resolution techniques have been used by many researchers in reconstructing high resolution image. The above resolution increasing techniques are researched under spatial and frequency domain. When increased in the resolution of image, it is very important to retain the quality of image, which is the challenging task in the domain of digital image processing. Here in this paper, the super resolution architecture for single low resolution technique has been proposed to reconstruct the high resolution image by combining interpolation and restoration methods in spatial domain. The modified adaptive bilinear interpolation is proposed for interpolation and contra harmonic mean & adaptive median filter are used for restoration of single low resolution image. The experimentation is done on standard data set show that, the results obtained from modified adaptive bilinear interpolation are competitively improved when compare to other existing single low resolution techniques in interpolation domain.

Cite This Paper

Suresha D, Prakash H N,"Natural Image Super Resolution through Modified Adaptive Bilinear Interpolation Combined with Contra Harmonic Mean and Adaptive Median Filter", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.8, No.2, pp.1-8, 2016. DOI: 10.5815/ijigsp.2016.02.01


[1]Rafael C. Gonzalez, Richard Eugene Woods, "Digital Image Processing", 3rd edition, Pearson. 

[2]Karl S. Ni., Truong Q. Nguyen, "An Adaptable k-Nearest Neighbors Algorithm for MMSE Image Interpolation", IEEE Transactions on Image Processing, Vol. 18, No. 9, September 2009.

[3]Shveta Chadda, Navjeet Kaur, Rajni Thakur, "Zooming Techniques for Digital Images: A survey", IJCST, Vol 3, Issue 1, Jan-Mar2012.

[4]Sapan Naik, Nikunj Patel, " Single Image Super Resolution in Spatial and Wavelet Domain", The International Journal of Multimedia & Its Applications (IJMA), Vol.5, No.4, August 2013.

[5]Jian Sun, Jian Sun, Zongben Xu, Heung-Yeung Shum, "Image Super-Resolution using Gradient Profile Prior". [Courtesy of]

[6]William T. Freeman, Thouis R. Jones, and Egon C. Pasztor, "Example-Based Super-Resolution", IEEE, March/April 2002.

[7]Assaf Zomet, Alex Rav, Acha Shmuel Peleg, "Robust Super-Resolution", IEEE 2001. [Courtesy of http://]

[8]Prakash P. Gajjar and Manjunath V. Joshi, "New Learning Based Super-Resolution: Use of DWT and IGMRF Prior", IEEE Transactions on Image Processing, Vol. 19, No. 5, May 2010, Page No: 1201-1213.

[9]Lingfeng Wang, Shiming Xiang, Gaofeng Meng, Huaiyu Wu and Chunhong Pan, "Edge-directed Single Image Super-resolution via Adaptive Gradient Magnitude Self-interpolation", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 23, No. 8, August 2013, Page No: 1289-1299.

[10]Amisha J. Shah, Suryakant B. Gupta, "Image Super Resolution-A Survey", 1st International Conference on Emerging Technology Trends in Electronics, Communication and Networking, 2012.

[11]Lexing Xie, "Image Restoration". [Courtesy of


[12]Alexey Lukin, Andrey S. Krylov, Andrey Nasonov, "Image Interpolation by Super-Resolution".[Courtesy of  _interpolation_by_super-resolution/links/02e7e5237b71e14092000000]

[13]Andrei Rares, Marcel J. T. Reinders, Jan Biemond, "Edge-Based Image Restoration", IEEE Transactions on Image Processing, Vol. 14, No. 10, October 2005.

[14]Taeg Sang Cho, C. Lawrence Zitnick, Neel Joshi, Sing Bing Kang, Richard Szeliski, William. T. Freeman, "Image restoration by matching gradient distributions", Digital Object Identifier 10.1109/TPAMI.2011.166, Pattern Analysis and Machine Intelligence, IEEE transactions,Volume:34,Issue:4, April 2012, Pages:683–694.

[15]Todd Wittman, "Mathematical Techniques for Image Interpolation". [Courtesy of http://public for Image Interpolation.pdf]

[16]Jian Sun, Nan-Ning Zheng, Hai Tao, Heung-Yeung Shum, "Image Hallucination with Primal Sketch Priors", Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference, Volume:2, 18-20 June 2003, Pages:II-729-736 .

[17]Gaurav Hansda, "Super-Resolution with Better Edge Enhancement ",University of Texas, Nov-2012.

[18]Jianchao Yang, John Wright, Yi Ma, Thomas Huang, "Image Super-Resolution as Sparse Representation of Raw Image Patches", Computer Vision and Pattern Recognition, CVPR 2008. IEEE Conference, 23-28 June 2008, Pages:1-8.

[19]Kwang In Kim and Younghee Kwon, "Single-Image Super-resolution using Sparse Regression and Natural Image Prior", Pattern Analysis and Machine Intelligence, IEEE Transactions, Volume:32 , Issue: 6 , June 2010, Pages:1127-1133.

[20]Jianchao Yang, Wright J. Huang, T.S. Yi Ma, "Image Super-Resolution Via Sparse Representation", Image Processing, IEEE Transactions, Volume:19 , Issue:11, 2010.

[21]Marco Bevilacqua, Aline Roumy, Christine Guillemot, Marie-Line Alberi Morel, "Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding". [Courtesy of Aline.Roumy/publi/12bmvc_Bevilacqua_lowComplexitySR.pdf]

[22]N/ superresolution/superresolution.pdf]eil Alldrin, "Super-Resolution". [Courtesy of

[23]Karl S. Ni, Sanjeev Kumar, Nuno Vasconcelos, Truong Q. Nguyen, "Single Image Super resolution based on Support Vector Regression", Acoustics, Speech and Signal Processing, ICASSP 2006 Proceedings. 2006 IEEE International Conference, Volume:2, 14-19 May 2006, Pages:II.

[24]Liang-Jian Deng, Weihong Guoy, Ting-Zhu Huang, "Single Image Super-Resolution via an Iterative Reproducing Kernel Hilbert Space Method".[Courtesy of]

[25]Qiang Zhou, Shifeng Chen, Jianzhuang Liu, Xiaoou Tang," Edge-Preserving Single Image Super-Resolution". [Courtesy of /mm11_edge_preserving_SR.pdf]

[26]Lyndsey C. Pickup, "Machine Learning in Multi-frame Image Super-resolution", Michaelmas Term, 2007. [Courtesy of publications/2008/Pickup08/pickup08.pdf]

[27]Jian Sun, Jiejie Zhu, Marshall F. Tappen, "Context-Constrained Hallucination for Image Super-Resolution", Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference, 13-18 June 2010, Pages: 231–238.

[28]Eran Gur, Zeev Zalevsky, "Single-Image Digital Super-Resolution A Revised Gerchberg-Papoulis Algorithm", IAENG International Journal of Computer Science, 34:2, IJCS_34_2_14, 2007. 

[29]Shengyang Dai, Mei Han, Ying Wu, Yihong Gong, "Bilateral Back-Projection for Single Image Super Resolution". Multimedia and Expo, 2007 IEEE International Conference,2-5 July 2007, Pages: 1039 – 1042.

[30]Oisin Mac Aodha, Neill D.F. Campbell, Arun Nair, and Gabriel J. Brostow, "Patch Based Synthesis for Single Depth Image Super-Resolution". [Courtesy of]

[31]Zhijun Fang, Naixue Xiong, Laurence T. Yang, Xingming Sun, and Yan Yang, "Interpolation-Based Direction-Adaptive Lifting DWT and Modified SPIHT for Image Compression in Multimedia Communications", IEEE systems journal, vol. 5, no. 4, December 2011, Page No: 584 -593.

[32]Turgay Celik and Tardi Tjahjadi, "Image Resolution Enhancement Using Dual-Tree Complex Wavelet Transform", IEEE geoscience and remote sensing letters, Vol. 7, No. 3, July 2010, Page No: 554- 557.

[33]Hasan Demirel and Gholamreza Anbarjafari, "Satellite Image Resolution Enhancement Using Complex Wavelet Transform", IEEE geoscience and remote sensing letters, Vol. 7,No.1,January 2010, Page No: 123- 126.

[34]Hasan Demirel and Gholamreza Anbarjafari, "IMAGE Resolution Enhancement by Using Discrete and Stationary Wavelet Decomposition", IEEE transactions on image processing, Vol. 20, No. 5, May 2011, Page No: 1458 – 1460.

[35]Shen Chuan Tai, Tse-Ming Kuo, Chon-Hong Iao, and Tzu-Wen Liao, "A Fast Algorithm for Single-Image Super Resolution in both Wavelet and Spatial Domain", 2012 International Symposium on Computer, Consumer and Control, 2012 IEEE, DOI 10.1109/IS3C.2012.182, Page No: 699- 702.