Joint Image De-noising and Enhancement for Satellite-Based SAR
This addresses image quality issues in satellite-based SAR imaging, but it is incremental as it combines existing techniques like CLAHE.
The paper tackles the problem of multiplicative noise and low contrast in SAR images, proposing a unified algorithm that combines de-noising and contrast enhancement, with verification using data from the ERS-2 satellite.
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.