Image Enhancement of Satellite Images Using Contrast Limited Adaptive Histogram Equalization and NLM

Abstract

Image enhancement is a crucial aspect of image processing research, aimed at improving the quality and visual appearance of images for various applications. This enhancement becomes particularly important in fields such as satellite imagery analysis, where images often suffer from poor contrast, noise, and other imperfections. In this work, a novel approach combining the Non-Local Means Filter (NLM) with Contrast Limited Adaptive Histogram Equalization (CLAHE) is proposed to address these challenges and enhance satellite images effectively. The proposed method aims to enhance image features, eliminate blurriness and noise, increase contrast, and reveal finer details for improved human perception. By leveraging the complementary strengths of NLM and CLAHE, this approach offers superior results compared to existing techniques. The method is implemented and validated  using MATLAB, conducting comprehensive tests to assess its performance. Experimental results demonstrate the effectiveness of our proposed technique, with average Peak Signal-to-Noise Ratio (PSNR) and Entropy values of 65.8360 and 7.5764, respectively. These results indicate significant improvements in image quality and highlight the potential of the approach for enhancing satellite imagery and other applications reliant on image enhancement techniques.