COLOR SATELLITE IMAGES DENOISING USING WAVELETS
Main Article Content
Abstract
The satellite image is multi band image,the first three bands have the largest wavelength and image information and usually contain noise due to different reason such as image band acquisition or transmission. In this paper an adaptive method implemented to denoising the satellite image by
using the Haar wavelet transform applied to the principle components bands of the satellite image.
The image denoising by Haar wavelet transform is applied on the first band(PC1).This band has found contain about 90% of the image information, in this case the time required for processing and storage size are reduced ,and the image appearance are more suitable than the processing the image bands directily.
Article Details
How to Cite
Publication Dates
References
Scoott E Umbaugh(1998), ”Computer Vision and Image Processing”, Prentice Hall.
ERDAS Inc(1995).,”Graphical models reference guide”, ERDAS Inc., Atlanta, Georgia.
Gomies(1997) “Image Processing and Computer Graphics “,Springer.
R.Gonzalez and P.Wintz(2001),” Digital Image Processing”second Edition , Addision – Wesley, Pub Comp.
Maarten Jansen(2001). "Noise Reduction by Wavelet Thresholding", volume 161. Springer Verlag,United States of America, 1 edition.
Martin Vetterli S Grace Chang, Bin Yu(2000). "Adaptive wavelet thresholding for image denoising and compression". IEEE Transactions on Image Processing, 9(9):1532–1546.
Jonathan Y. Stein(2000)," Digital Signal Processing: A Computer Science Perspective",John Wiley & Sons, Inc.
Pujita Pinnamaneni(2003),"3-D Wavelet Transformation in Java", Dept of Computer Science,Mississippi State University.
Colm Mulcahy(2004),"Image Compression using the Haar Wavelet transform", Spelman Science and Math Journal.
Raghuram Rangarajan(2002)," Image Denoising Using Wavelets".
Gabriel Cristobal, Monica Chagoyen, Boris Escalante-Ramirez, Juan R Lopez, “Wavelet-based denoising methods, A comparative study with applications in microscopy”, Proc. SPIE’s International Symposium on Optical Science, Engineering and Instrumentation,Wavelet Applications in Signal and Image Processing IV,Vol. 2825, 1996.
R. Wilson and A.D. Calway. A general multiresolution signal descriptor and its application to image analysis. In Signal Processing, pages 663{666. EURASIP, 1988