Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

Super resolution of remote sensing image based on structure similarity in CS frame

[+] Author Affiliations
Zongxu Pan, Huijuan Huang, Weidong Sun

Tsinghua Univ. (China)

Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80020H (December 08, 2011); doi:10.1117/12.902613
Text Size: A A A
From Conference Volume 8002

  • MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis
  • Zhiguo Cao; Aaron Fenster; Laszlo G. Nyul; Chao Cai
  • Guilin, China | November 04, 2011

abstract

In this paper, a novel super resolution (SR) method for remote sensing images based on compressive sensing (CS), structure similarity and dictionary learning is proposed. The basic idea is to find a dictionary which can represent the high resolution (HR) image patches in a sparse way. The extra information coming from the similar structures which often exist in remote sensing images can be learned into the dictionary, so we can get the reconstructed HR image through the dictionary in the CS frame due to the redundance in the image which has a sparse form in the dictionary. We use K-SVD algorithm to find the dictionary and OMP method to reveal the sparse coding coefficient's location and value. The difference between our method and the previous sample-based SR method is that we only use low-resolution image and the interpolation image from itself rather than other HR images. Experiments on both optical and laser remote sensing images show that our method is better than the original CS-based method in terms of not only the effect but also the running time.

© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Zongxu Pan ; Huijuan Huang and Weidong Sun
"Super resolution of remote sensing image based on structure similarity in CS frame", Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80020H (December 08, 2011); doi:10.1117/12.902613; http://dx.doi.org/10.1117/12.902613


Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.