Abstract
In this paper, an image resolution enhancement algorithm based on wavelet transform is proposed. The DWT-SWT uses the well known image resolution enhancement algorithm based on wavelet decomposition. The main focus of this paper lies in the optimization of DWT-SWT wavelet filters based on parameters related to edges in the image. Initially all the input images are classified into various bins based on the edges present in the image and each bin of images will be enhanced by applying unique wavelet filters. This library of wavelet filters are evolved using bio-inspired algorithm like genetic algorithm considering individual image bins. The individual image groups of satellite images are created based on the spatial frequency mean (SFM) and DWT-SWT wavelet filters are evolved for each groups for both near edge and far edge image namely local and global DWT-SWT filters. These enhancement algorithms are based on existing DWT-SWT based methods are proposed to improve the resolution of the low-resolution satellite images. The proposed algorithms suitably enhance the resolution of the image shows a significant improvement in the PSNR compared with the existing techniques.