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Journal of Nanomaterials
Volume 2014, Article ID 931616, 6 pages
Research Article

A New Method for Superresolution Image Reconstruction Based on Surveying Adjustment

1School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
2College of Traffic Information, Hunan Communication Polytechnic, Changsha, Hunan 410132, China

Received 24 April 2014; Accepted 24 May 2014; Published 9 June 2014

Academic Editor: Yongfeng Luo

Copyright © 2014 Jianjun Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A new method for superresolution image reconstruction based on surveying adjustment method is described in this paper. The main idea of such new method is that a sequence of low-resolution images are taken firstly as observations, and then observation equations are established for the superresolution image reconstruction. The gray function of the object surface can be found by using surveying adjustment method from the observation equations. High-resolution pixel value of the corresponding area can be calculated by using the gray function. The results show that the proposed algorithm converges much faster than that of conventional superresolution image reconstruction method. By using the new method, the visual feeling of reconstructed image can be greatly improved compared to that of iterative back projection algorithm, and its peak signal-to-noise ratio can also be improved by nearly 1 dB higher than the projection onto convex sets algorithm. Furthermore, this method can successfully avoid the ill-posed problems in reconstruction process.