Curvelet Image Fusion using Neural Network and SVM Algorithm

Volume: 3    Issue: 2

Year of Publication: 2016

Pages: (16-20)

Authors: Monika Kumari, Mr. Sanjay Yadav

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Abstract

This paper describes a novel image fusion process which is suitable for pan-sharpening of multispectral (MS) groups furthermore in view of multi-resolution analysis. The combination of high-spectral but low spatial resolution multispectral and low-spectral but high spatial resolution panchromatic satellite images are exceptionally helpful methods in different uses of remote sensing. A few studies demonstrated showed that wavelet-based image fusion strategy gives high quality of the spectral content of the fused image. In this paper we present another method based on the Curvelet transform utilizing Neural Network and SVM which represents edges better than wavelets and since edges play a vital role in image understanding and one great approach to enhance spatial resolution is to upgrade the edges then Curvelet-based image fusion method provides richer information in the spatial and spectral domains simultaneously. We will perform image fusion using Curvelet Transform with Neural Network and SVM Techniques. This new technique has reached an optimum fusion result.

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Keywords

Edge detection, Fusion, Multiresolution analysis, Wavelet transform, Curvelet transform.