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.

Date Published: 19 February 2008
PDF: 9 pages
Proc. SPIE 6625, International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications, 662510 (19 February 2008); doi: 10.1117/12.791023

Published in SPIE Proceedings Vol. 6625:
International Symposium on Photoelectronic Detection and Imaging 2007: Related Technologies and Applications
Liwei Zhou, Editor(s)