OcrV1, France, Analysis, bibRecord, 000024

Deblurring of Document Images Based on Sparse Representations Enhanced by Non-local Means

Identifieur interne : 000024 ( France/Analysis ); précédent : 000023; suivant : 000025

Deblurring of Document Images Based on Sparse Representations Enhanced by Non-local Means

Auteurs : Nibal Nayef [France] ; Petra Gomez-Kr Mer [France] ; Jean-Marc Ogier [France]

Source :

RBID : Hal:hal-01315620

Abstract

Blur is one of the most difficult distortions incamera captured documents. It degrades the visual quality of animage, and makes it difficult to read whether by a human or OCRsystems. This paper presents a novel non-blind deblurring methodthat combines the well known effective techniques of sparse representations and non-local image similarity. The presented problemformulation enables the use of standard sparse coding methodsfor solving sparse coding-based deblurring when enhanced bya non-local means prior. The method has been tested on bothsynthetic and real document images degraded with a variety ofblur kernels. The resulting deblurred images have high qualityin terms of both signal-to-noise ratio and OCR accuracy.

Url:

https://hal.archives-ouvertes.fr/hal-01315620

DOI: 10.1109/ICPR.2014.760

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Hal, to step Corpus: 000038
to stream Hal, to step Curation: 000038
to stream Hal, to step Checkpoint: 000025
to stream Main, to step Merge: 000064
to stream Main, to step Curation: 000064
to stream Main, to step Exploration: 000064
to stream France, to step Extraction: 000024

Links to Exploration step

Hal:hal-01315620

Le document en format XML

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<front><div type="abstract" xml:lang="en">Blur is one of the most difficult distortions incamera captured documents. It degrades the visual quality of animage, and makes it difficult to read whether by a human or OCRsystems. This paper presents a novel non-blind deblurring methodthat combines the well known effective techniques of sparse representations and non-local image similarity. The presented problemformulation enables the use of standard sparse coding methodsfor solving sparse coding-based deblurring when enhanced bya non-local means prior. The method has been tested on bothsynthetic and real document images degraded with a variety ofblur kernels. The resulting deblurred images have high qualityin terms of both signal-to-noise ratio and OCR accuracy.</div>
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   |wiki=    Ticri/CIDE
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   |texte=   Deblurring of Document Images Based on Sparse Representations Enhanced by Non-local Means
}}

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Deblurring of Document Images Based on Sparse Representations Enhanced by Non-local Means

Deblurring of Document Images Based on Sparse Representations Enhanced by Non-local Means

Source :

Abstract

Links toward previous steps (curation, corpus...)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri