Satellite/Aerial Image Compression Using Adaptive Block Truncation Coding Technique

Abstract

Satellite/aerial images taken from high altitude contain large amount of pixels to store accurate information. These high resolution images require large storage capacity and more transmission time. Applying an efficient compression technique on these images can reduce high storage capacity requirement and transmission time. In this paper block truncation coding (BTC) based color image compression technique for aerial/satellite images is proposed. High degree of correlation among the RGB planes of a color image can be reduced by converting these planes into HSV planes. Each of the H and S planes are encoded using BTC with quad clustering and V plane is encoded with BTC based bi-clustering or tri-clustering depending on the edge information present in the plane. The effectivity of the proposed method is validated by comparing it with the conventional BTC and its variant methods. Experimental analysis indicate that the proposed method is superior to other state of the art methods both in terms of visual quality and quantitative metrics.