Implementing Fast-Haar Wavelet transform on original Ikonos images to perform image fusion: qualitative assessment

Abstract

This article presents the Fast Haar Wavelet Transform (FHWT) algorithm applied to satellite-images fusion. FHWT is applied to both a multispectral image and a panchromatic Ikonos image using the digital image processing toolbox and wavelet toolbox provided by MatLab®. The results of the fusion are analyzed and evaluated quantitatively. Regarding the quantitative results of the fusion, first the mathematical-statistical correlation algorithm is used to analyze the spectral and spatial gain of the merged images. Next, the kappa coefficient is analyzed on three samples taken from the merged images, which are binarized in order to identify their spatial accuracy. It is shown that FHWT outperforms other predefined wavelets (namely rbio6.8, bior6.8, db7, dmey and haar) when merging the images. Moreover, merged images maintain the same spectral output as the original image, and also exhibit significant spatial resolution gain.

Keywords

• image fusion
• fast haar wavelet transform (FHWT)
• RGB-IHS transformation
• mallat’s algorithm
• IKONOS Images
• Wavelet transform