Satellite Image Resolution Enhancement Using Dual-Tree Complex Wavelet Transform and Adaptive Histogram Equalization
M. Merlin Bhakiya, Nellutla Sasikala · 2014
Satellite images are used in many applications such as geosciences studies, astronomy, and geographical information systems. One of the most important quality factors in images comes from its resolution. Interpolation in image processing is a well- known method to increase the resolution of a digital image. Interpolation has been widely used in many image-processing applications such as facial reconstruction, multiple-description coding, and resolution enhancement. In this project, we propose a new satellite image resolution enhancement technique based on the interpolation of the high-frequency sub bands obtained by dual tree complex wavelet (DTCWT) transform and the input image. The proposed resolution enhancement technique uses DTCWT to decompose the input image into different sub-bands. Then, the high-frequency sub-band images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new resolution-enhanced image by using inverse DTCWT. In order to achieve a sharper image, an intermediate stage for estimating the high-frequency sub bands has been proposed. The proposed technique has been tested on satellite benchmark images. The quantitative peak signal-to-noise ratio and root mean square error and visual results show the superiority of the proposed technique over the conventional and state- of-art image resolution enhancement techniques. Adaptive Histogram Equalization is the algorithm which have improved the image resolution. The PSNR improvement of the proposed technique is up to 19.79 dB.