A method of super-resolution reconstruction for remote sensing image based on non-subsampled contourlet transform

被引：0
作者：
Zhou, Jinghong [1 ]
Zhou, Cui [1 ]
Zhu, Jianjun [1 ]
Fan, Donghao [1 ]
机构：
[1] School of Geosciences and Info-Physics, Central South University, Changsha, 410083, Hunan
来源：
Guangxue Xuebao/Acta Optica Sinica | 2015年 / 35卷 / 01期
关键词：
Bicubic interpolation; Image processing; Non-subsampled contourlet transform; Regional adaptive fusion; Super-resolution reconstruction; Two-dimensional wavelet transform;
D O I：
10.3788/AOS201535.0110001
中图分类号：
学科分类号：
摘要：
An improved method is proposed to solve the existing problem that the fusion process is too simple in non- subsampled contourlet transform (NSCT) super- resolution reconstruction. The magnitude of the spatial frequency reflects the degree of image detail richness, and the improved method uses this magnitude of regional window as the standard of the weight, so the adaptive weighted fusion method is applied to the obtained high frequency by NSCT decomposition of image. The adaptive weighted fusion method and NSCT analysis are assembled to achieve image super- resolution reconstruction, in this process, each corresponding high-frequency image is fused by adaptive weighted fusion method, and the low-frequency image is processed to get a mean. The super- resolution image is acquired by inverse NSCT to both the low frequency images and high frequency images. Through simulation and engineering practice, the improved method proves to be feasible and effective. ©, 2015, Chinese Optical Society. All right reserved.
引用
收藏
页数：9
相关论文
共 25 条
  • [1] Xu Z., Liu J., Long K., Et al., Accuracy analysis of focusing mechanism of high resolution space camera, Acta Optica Sinica, 33, 7, (2013)
  • [2] Sun T., Lin L., Sun F., Et al., The Optical Remote Sensing Image Restoration and Super-Resolution Reconstruction, (2012)
  • [3] Tan B., Xu Q., Xing S., Et al., Wavelet super-resolution algorithm and its application to SPOT images, Acta Geodaetica et Cartographica Sinica, 33, 3, pp. 233-238, (2004)
  • [4] Liu J., Jin M., Ma R., Et al., Novel deterministic simple 0- 1 observation matrix and wavelet sparsity based compressed sensing implementation method for embedded vision system, Chinese J Lasers, 40, 11, (2013)
  • [5] Zhou Y., Li X., Zhao L., Modified linear-prediction based band selection for hyperspectral image, Acta Optica Sinica, 33, 8, (2013)
  • [6] Huang D., Yang M., Xu H., Et al., Fusion of multi-spectral and panchromatic images using optimal estimation theory, Geomatics and Information Science of Wuhan University, 36, 9, pp. 1039-1042, (2011)
  • [7] Coifman R.R., Donoho D.L., Translation-Invariant De-Noising, (1995)
  • [8] Do M.N., Vetterli M., Contourlets: A directional multiresolution image representation, 1, 1, pp. 357-360, (2002)
  • [9] Burt P., Adelson E., The Laplacian pyramid as a compact image code, IEEE Transactions on Communications, 31, 4, pp. 532-540, (1983)
  • [10] Bamberger R.H., Smith M.J.T., A filter bank for the directional decomposition of images: Theory and design, IEEE Transactions on Signal Processing, 40, 4, pp. 882-893, (1992)
123