Joint Image De-noising and Enhancement for Satellite-Based SAR

TL;DR

This paper introduces a unified algorithm for simultaneous de-noising and contrast enhancement of SAR images, improving their quality for better information extraction from satellite data.

Contribution

It presents a novel combined approach integrating de-noising and CLAHE-based contrast enhancement specifically for SAR images.

Findings

Effective noise reduction demonstrated on satellite data

Enhanced image contrast improves feature visibility

Algorithm validated with ESA ERS-2 satellite data

Abstract

The reconstructed images from the Synthetic Aperture Radar (SAR) data suffer from multiplicative noise as well as low contrast level. These two factors impact the quality of the SAR images significantly and prevent any attempt to extract valuable information from the processed data. The necessity for mitigating these effects in the field of SAR imaging is of high importance. Therefore, in this paper, we address the aforementioned issues and propose a technique to handle these shortcomings simultaneously. In fact, we combine the de-noising and contrast enhancement processes into a unified algorithm. The image enhancement is performed based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) technique. The verification of the proposed algorithm is performed by experimental results based on the data that has been collected from the European Space Agency's ERS-2 satellite which operates in strip-map mode.