Title :
Remote sensing image fusion using best bases sparse representation
Author :
Iqbal, Mahboob ; Chen, Jie ; Wen, Xian-Zhong ; Li, Chun-Sheng
Author_Institution :
Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
Abstract :
A new technique based on best bases sparse representation is proposed for fusion of remote sensing images. In order to carry out multi-resolution image fusion, low-resolution image is upscaled to match resolution of high-resolution images. Corresponding patches from remote sensing images are represented by finding out best bases from over-complete dictionaries comprising of elements derived from basis function of DCT, Wavelets, ridgelets, and curvelets. The corresponding bases of image patches are combined based on local information parameter (LIP) derived from respective patches. The use of LIP helps ensure transfer of details in high-resolution image into fused image.
Keywords :
discrete cosine transforms; geophysical image processing; image fusion; image matching; image representation; image resolution; remote sensing; wavelet transforms; DCT function; LIP; best bases sparse representation; curvelet function; high-resolution images; image patches; local information parameter; low-resolution image; multiresolution image fusion; remote sensing image fusion; resolution match; ridgelet function; wavelet function; Abstracts; Argon; Frequency modulation; Image resolution; Optical imaging; Optical sensors; Remote sensing; Fusion; Over-complete Dictionaries; Pan-sharpening; Remote Sensing; Sparse Representation;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2012.6352378
