Efficient analysis of hybrid directional lifting technique for satellite image denoising

Abstract

Satellite images are often corrupted by noise in the acquisition and transmission process. While removing noise from the image by attenuating the high frequency image components, it removes some important details as well. In order to improve the visual appearance and retain the useful information of the images, an effective denoising technique is required to reduce the noise level. For denoising, many researches exploit the directional correlation in either spatial or frequency domain. However, the orientation estimation for directional correlation becomes inefficient and error prone in noised circumstances. This paper proposes a new hybrid directional lifting (HDL) technique for image denoising that involves pixel classification and orientation estimation, along with adding small amount of noise, in order to improve the performance efficiency of the technique. Experimental results show that the HDL technique improves both peak signal to noise ratio and visual quality of images with rich textures.