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Paper Details

Analysis of the Effect of Incidence Angle variation in Fusion of SAR images with Multispectral image using Empirical Mode Decomposition

A. Dalrin Ampritta, S. S. Ramakrishnan

Journal Title:International Journal of Renewable Energy and Environmental Engineering
Abstract


In the field of Remote Sensing and GIS, colour images of high resolution in the form of aerial photos or satellite images are desired for visually interpreting various features in our environment, but are limited due to their expensiveness. On the other hand, SAR images of high resolution are available at a comparatively lower cost. With the increasing demand for better image quality, lot of image processing algorithms have been designed for analyzing optical and SAR images. In the image fusion process multi-sensor outputs can be combined to give a better quality image of the area. The purpose of fusion process is to synthesize a new multispectral image, whose bands coincide as much as possible with those of the original multispectral image, and with a spatial resolution comparable to the radar image. Currently, the most used image fusion techniques are IHS (Intensity Hue Saturation), Wavelet Transform, and PCA (Principal Component Analysis). It is evident that the employed methods seem to work well for single-sensor, single-date fusion. However with radar and multispectral data from different sensors or dates, these fusion methods create images of higher spatial resolution, but usually at the cost of the original colour or spectral characteristics of the input images. This is especially true if two completely different sensors are used. So new algorithms are required to overcome these problems and establish superiority over the standard fusion techniques. In this paper, the effect of variation in incidence angle of three SAR images which are fused separately with the multispectral image is studied. The analysis is done based on the capability of performing visual land use interpretation using each of the fused images. For the fusion process, a new algorithm based on 2D EMD (Two Dimensional Empirical Mode Decomposition) is coded using Matlab software. EMD is a non-parametric data-driven analysis tool that decomposes the single band radar image into high frequency IMFs (Intrinsic Mode Functions).This algorithm then combines the IMFs generated from the radar (SAR) image with the optical (multispectral) image, thus obtaining the fused image. The implementation of this algorithm is done by using ERS 2 SAR and Landsat ETM+ images of Mansadevi region in Himachal Pradesh, India. Finally, Quality assessment of Empirical Mode Decomposition Algorithm with Conventional Fusion Techniques is done by using a statistical metric technique Universal Image Quality Index.

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