Digital Image Restoration & Restoration of Burned image & Documents Using DigitalImage Processing: Possibilities and Limitations

Abstract

Digital image restoration of burnt or charred documents is a critical challenge in forensic and archival studies. This research proposes a Python-based approach to restore burnt images into their original, readable digital form. The method utilizes advanced image processing techniques, including noise removal, contrast enhancement, edge detection, and morphological operations, combined with deep learning-based inpainting models. The approach successfully reconstructs partially destroyed regions, recovers textual and graphical information, and enhances overall visual quality. Experimental results demonstrate that the proposed method significantly improves the readability of damaged images, offering an effective solution for digital preservation, forensic investigation, and document recovery applications.