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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Publications Copernicus
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Citation
Articles | Volume X-3-2024
https://doi.org/10.5194/isprs-annals-X-3-2024-245-2024
https://doi.org/10.5194/isprs-annals-X-3-2024-245-2024
04 Nov 2024
 | 04 Nov 2024

Comparing inpainting techniques for urban object restoration from orbital images

Eduardo Soares Nascimento, Allan Alves Lopes Ferreira, Guilherme Pina Cardim, Pedro Pina, and Erivaldo Antonio da Silva

Keywords: inpainting, roads, mathematical morphology, digital image processing, remote sensing images

Abstract. Based on the comparison of three established inpainting techniques, namely Criminisi, Beltamio, and Galerne and Leclaire, our study aimed to identify the most effective method for road restoration after extraction and detection using a Mathematical Morphology operators combined with hybrid techniques of digital image processing in remote sensing images. While all techniques were evaluated based on both visual analysis and quantitative metrics, the Criminisi approach emerged as the better choice. Despite introducing some additional noise, this technique demonstrated superior performance in terms of Completeness and overall Quality, achieving approximately 95.23% and 94.56%, respectively. Its ability to accurately reconstruct linear geometries while effectively removing existing noise highlighted its suitability for road restoration tasks.