Interpolation of Multi-Spectral Images Inwavelet Domain for Satellite Image Fusion

This paper presents an image interpolation technique for satellite image fusion in the wavelet domain. For the fusion of satellite images, we need to interpolate and match the low resolution multi-spectral images (MSIs) to the high resolution panchromatic images. But since the typical spline-based interpolation methods employed in the conventional image fusion entails blurriness of edges, we propose a wavelet-domain image interpolation method that creates high frequency details based on the estimation of non-existent higher band coefficients from the relationship of available coefficients in lower scales. We model the relationship of coefficients in vertical as well as horizontal direction by the Markov stochastic model, and also find the coefficients of higher scale in this respect. The estimated coefficients are further refined by adding the maximum a posteriori (MAP) estimation process. The proposed interpolation technique is employed into the most popular image fusion algorithms, namely wavelet, principle component analysis (PCA), and intensity-hue-saturation (IHS) transformation based algorithms, instead of the conventional bilinear or bicubic interpolation methods. The experimental results show that the fused image based on the proposed interpolation instead of the conventional bilinear and bicubic interpolation algorithms employed in the conventional wavelet, principle component analysis (PCA), and intensity-hue-saturation (IHS) transformation based fusion algorithms, we incorporate the proposed wavelet based interpolation method.