Blind deblurring of hyperspectral document images
| Autor: | Ljubenovic, M., Guzzonato, P., Franceschin, G., Traviglia, A. |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | In: Image Analysis and Processing. ICIAP 2022 Workshops. Lecture Notes in Computer Science, vol. 13373. Springer, Cham (2022) |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1007/978-3-031-13321-3\_14 |
| Popis: | Most computer vision and machine learning-based approaches for historical document analysis are tailored to grayscale or RGB images and thus, mostly exploit their spatial information. Multispectral (MS) and hyperspectral (HS) images contain, next to the spatial information, much richer spectral information than RGB images (usually spreading beyond the visible spectral range) that can facilitate more effective feature extraction, more accurate classification and recognition, and thus, improved analysis. Although utilization of rich spectral information can improve historical document analysis tremendously, there are still some potential limitations of HS imagery such as camera-induced noise and blur that require a carefully designed preprocessing step. Here, we propose novel blind HS image deblurring methods tailored to document images. We exploit a low-rank property of HS images (i.e., by projecting an HS image to a lower dimensional subspace) and utilize a text tailor image prior to performing a PSF estimation and deblurring of subspace components. The preliminary results show that the proposed approach gives good results over all spectral bands, removing successfully image artefacts introduced by blur and noise and significantly increasing the number of bands that can be used in further analysis. Comment: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101026453. This work is published in the Lecture Notes in Computer Science book series (LNCS, volume 13373) as part of the Image Analysis and Processing, ICIAP 2022 Workshops |
| Databáze: | arXiv |
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