A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Wavelet-based image denoising using a Markov random field a priori model
IEEE Transactions on Image Processing
Multisource images analysis using collaborative clustering
EURASIP Journal on Advances in Signal Processing
EURASIP Journal on Advances in Signal Processing - Special issue on theory and application of general linear image processing
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Synthetic aperture radar (SAR) imaging sensor presents an important advantage for the earth change observation independently of weather conditions. However, the SAR image provides an incomplete information (as roads) of the observed scene leading thus to an ambiguous interpretation. In order to compensate the lack of features, the high spatial resolution panchromatic (P) image is often used as a complementary data for improving the quality of the SAR image. The concept is based on the extraction of features (details) from the P image in order to incorporate into the SAR image. Therefore, we propose an approach based on the use of the à trous wavelet decomposition (ATWD) for extracting features from the P image. Experimental results show that the SAR-P composite image allows a better detection of lines, edges, and field boundaries.