Satellite image contrast enhancement algorithm based on Plateau Histogram Equalization

Abstract

The quality of remotely sensed satellite images depends on the reflected electromagnetic radiation from earth surface features. Lack of consistent and similar amounts of energy reflected by different features from earth surface, results a low contrast satellite image. Enhancement of contrast is needed for satellite images to identify and extract objects from images, where features are essential in studying earth applications. In this paper, a new contrast enhancement technique for satellite images based on clipping or plateau histogram equalization has been proposed. The technique adopted Bi-Histogram Equalization with Plateau Limit (BHEPL) for image decomposition and Self-Adaptive Plateau Histogram Equalization (SAPHE) for threshold calculation. The proposed method has been compared with existing methods such as Histogram Equalization (HE), Brightness Preserving Bi-Histogram Equalization (BBHE), Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE), Dynamic Histogram Equalization (DHE), Bi-Histogram Equalization with Plateau Limit (BHEPL) and Self-Adaptive Plateau Histogram Equalization (SAPHE) with image quality measures such as Absolute Mean Brightness Error (AMBE) and Peak-Signal to Noise Ratio (PSNR). � 2014 IEEE.