The Review of Prospect of Remote Sensing Image Processing

Title:The Review of Prospect of Remote Sensing Image Processing

Volume: 10 Issue: 1

Author(s): Wenzhong Zhu*, Hualong Jiang, Shuwen Zhou and Mike Addison

Affiliation:

• School of Computer Science, Sichuan University of Science, Zigong,China

Keywords: Remote sensing, image processing technology, edge detection, SAR images, PCA, wavelet transform.

Abstract: Background: In order to further analyze the problems of remote sensing image processing technology and the future development direction, this paper analyzes the concept of remote sensing and basic process, describes the status of domestic and international development of remote sensing image processing technology, as described in various patents.

Method: Several key elements of remote sensing image processing technology are studied, including five directions, remote sensing image matching, the integration of infrared and visible light remote sensing image, edge detection of SAR images, remote sensing image classification and remote sensing image change detection, and research and development status of these five directions were analyzed. The main characteristics of remote sensing image processing technology and reasons constraining the development of remote sensing image processing technology are analyzed.

Result: Image fusion method based on PCA, are relatively vague and inaccurate. The image fusion method based on wavelet transform is used for image fusion, the fusion result is clear, and the image fusion method based on wavelet transform is more accurate than PCA.

Conclusion: The comparison results of different methods are given by computer simulation experiment; it provides a reference for the development trends and application prospects of remote sensing image processing technology.

Cite this article as:

Zhu Wenzhong*, Jiang Hualong, Zhou Shuwen and Addison Mike, The Review of Prospect of Remote Sensing Image Processing, Recent Patents on Computer Science 2017; 10 (1) . https://dx.doi.org/10.2174/2213275909666160616115416

DOI https://dx.doi.org/10.2174/2213275909666160616115416	Print ISSN 2213-2759
Publisher Name Bentham Science Publisher	Online ISSN 1874-4796