An improved approach to remove cloud and mist from remote sensing images based on the Mallat algorithm

Xifang Zhou; Feng Wu

doi:10.1117/12.791023

19 February 2008 An improved approach to remove cloud and mist from remote sensing images based on the Mallat algorithm

Xifang Zhou, Feng Wu

Proceedings Volume 6625, International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications; 662510 (2008) https://doi.org/10.1117/12.791023
Event: International Symposium on Photoelectronic Detection and Imaging: Technology and Applications 2007, 2007, Beijing, China

Abstract

This article proposes an effective method for removing the thin cloud and mist in the remote sensing images using Mallat algorithm by analyzing the frequency distribution characteristics of the remote sensing images influenced by cloud and mist. Based on the characteristics of relatively lower frequency of the cloud and fog, relatively higher frequency of the scenes, and the multi-resolution of the wavelet function, we analyze the characteristics of the wavelet transformation in both the theory and the practical application, and conclude that the detail coefficient at the lower level of the wavelet represents relatively high-frequency of the image, the detail coefficient at its higher level represents the relatively low frequency band of the image. Like this, we can effectively strengthen the high-frequency components and weaken the low frequency components in the images, achieve goal for removing cloud and mist. The experimental results of the proposed algorithm are found to be satisfactory.

Citation Download Citation

Xifang Zhou and Feng Wu "An improved approach to remove cloud and mist from remote sensing images based on the Mallat algorithm", Proc. SPIE 6625, International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications, 662510 (19 February 2008); https://doi.org/10.1117/12.791023

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available