Beyond Pixels: Sentiment-Based Assessment of Image Inpainting Techniques with Application to Forgery Removal

Inpainting is an image processing technique used to remove alterations and restore the original content of a modified image. The effectiveness of inpainting can be evaluated through various methods, increasingly based on criteria related to human perception. In this work, we propose a methodology to assess the effectiveness of different inpainting techniques from the perspective of an image's emotional value. We apply Visual Sentiment Analysis (VSA) algorithms to determine which techniques are most effective in restoring the original emotional value of modified images. The goal is to identify the most suitable methods for removing common image modifications, specifically manipulated elements, while preserving the image's original sentiment. This analysis is particularly relevant for assessing the communicative impact of modified images and understanding the emotional value of such alterations.