Abstract
High Resolution Satellite Images are of a significant importance in many fields of research. For the last few decades Wavelets are playing a key role in image resolution enhancement techniques. In those algorithms, Discrete Wavelet Transform (DWT) is mostly used in image decomposition stage and bicubic interpolation is used in interpolation stage. In this paper, we proposed a new technique based on the image decomposition using DWT and the interpolation using Gaussian Mixture Model (GMM) which is a parametric probability density function represented as a weighted sum of Gaussian component densities instead of weighted sum of neighborhood pixels such as bicubic or bilinear interpolations. This DWT image decomposition and GMM interpolation gives better results than existing techniques and it is proved with the quantitative (peak signal-to-noise ratio and quality index) and visual results over the conventional and state-of-art image resolution enhancement techniques.
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