International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
Volume 121 - Issue 14 |
Published: July 2015 |
Authors: Maninder Kaur, Pooja |
![]() |
Maninder Kaur, Pooja . Wavelet and Curvelet Transformation based Image Fusion with ANFIS and SVM. International Journal of Computer Applications. 121, 14 (July 2015), 13-19. DOI=10.5120/21607-4639
@article{ 10.5120/21607-4639, author = { Maninder Kaur,Pooja }, title = { Wavelet and Curvelet Transformation based Image Fusion with ANFIS and SVM }, journal = { International Journal of Computer Applications }, year = { 2015 }, volume = { 121 }, number = { 14 }, pages = { 13-19 }, doi = { 10.5120/21607-4639 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2015 %A Maninder Kaur %A Pooja %T Wavelet and Curvelet Transformation based Image Fusion with ANFIS and SVM%T %J International Journal of Computer Applications %V 121 %N 14 %P 13-19 %R 10.5120/21607-4639 %I Foundation of Computer Science (FCS), NY, USA
The Image fusion is a data fusion innovation which keeps images as main research substance which refers to the strategies that integrate multi-images of the same scene from multiple image sensor data or integrate multi images of the same scene at different times from single image sensor. In this paper we describes a novel image fusion method, is suitable for pan-sharpening of multispectral (MS) bands which are based on multi-resolution analysis. The low-resolution MS bands are sharpened by injecting high-pass directional details extracted from the high-resolution panchromatic (Pan) image by means of the Wavelet and Curvelet transform, which is a non-separable MRA, whose basis function are directional edges with progressively increasing resolution. We introduce a new method based on the Wavelet and Curvelet transform using Neural Network which represents edges better than wavelets in this paper. Therefore, edges play a fundamental role in image understanding and one important way to enhance spatial resolution is to enhance the edges. Wavelet and Curvelet-based image fusion method provides richer information in the spatial and spectral domains simultaneously