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Image Resolution Improvement Using Image Loss Information  

Kim, Won-Hee (부경대학교 컴퓨터공학과)
Kim, Jong-Nam (부경대학교 컴퓨터공학과)
Abstract
Image resolution improvement is commonly technique for applications such as image reconstruction or enlargement. It is important to remove image quality degradation such as blocking effect or artificiality occurrence. In this paper, we propose image resolution improvement method using loss information of image. The proposed compute and estimate by low level interpolation of obtained low resolution image, it is applied by interpolated high resolution as 1-stage interpolation. We generate last interpolation image by iteration of error computation and application between obtained low resolution image and 1-stage interpolation image. By experiments using same test images, we confirmed improvement over 3.2dB of average PSNR and enhancement of subject image quality. Also, we can reduce more than 85% computation complexity. The proposed image resolution improvement method may be helpful for various applications of image processing.
Keywords
Loss Information; Image Resolution Enhancement; Image Interpolation; Image Improvement;
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1 W. Qing and R. K. Ward, "A New Orientation- Adaptive Interpolation Method," IEEE Transactions on Image Processing, vol.16, Issue 4, pp.889-900 Apr. 2007.
2 S. Banerjee, "Low-Power Content-Based Video Acquisition for Super-Resolution Enhancement," IEEE Transactions on Multimedia, vol.11, Issue 3, pp.455-464, Apr. 2009.   DOI
3 K. I. Kim and Y. H. Kwon, "Example-based Learning for Single-Image Super-resolution," Lecture Notes in Computer Science, vol.5096, pp.456-465, Jun, 2008.
4 http://www.mathworks.com/matlabcentral/fileexchange/21410-increase-image-resolution.
5 A. Giachetti and N. Asuni, "Fast Artifacts-free Image Interpolation," In Proc. of the British Machine Vision Conf., pp.123-132, 2008.
6 N. Asuni, "INEDI -- Tecnica Adattativa Per I'interpolazione di Immagini," Master's thesis, Universita degli Studi di Cagliari, 2007.
7 O. Salvado, C. Hillenbrand, and D. Wilson. "Partial Volume Reduction by Interpolation with Reverse Diffusion," International Journal of Biomedical Imaging, vol.2006, pp.1-13, 2006.
8 S. H. Hong, R. H. Park, S. J. Yang, and J. Y. Kim, "Image Interpolation Using Interpolative Classified Vector Quantization," Image Vis. Comput., vol.26, no.2, pp.228-239, Feb. 2008.   DOI   ScienceOn