Implementation of interpolation method in reconstructing damaged satellite image caused by impulse noise

Background: Images are extensively utilized in fields such as engineering, health, and defense. During transmission, these images often lose quality due to noise interference. Aim: The primary objective of this study is to develop a method to effectively reduce salt and pepper noise, a common issue in image transmission, and restore images to their original state. Method: To achieve this, we propose using a numerical approach based on the interpolation method, specifically designed to address the noise reduction challenge. Result: Experimental application of the interpolation method on various images demonstrated that it significantly enhances the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) values, especially for images with low to medium noise density. Conclusion: Compared to other methods, our interpolation-based approach shows superior performance in reducing salt and pepper noise in images, making it a promising solution for image restoration in various applications.