2011
DOI: 10.1016/j.imavis.2011.01.001
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Enhancement of historical printed document images by combining Total Variation regularization and Non-local Means filtering

Abstract: This is an author-produced, peer-reviewed version of this article. produce an image with a cleaner background while keeping character details. The second step is applied to the cleaner image and consists of a filter based on non-local means: character edges are smoothed by searching for similar patch images in pixel neighborhoods. The document images to be enhanced are real historical printed documents from several periods which include several defects in their background and on character edges. These defects … Show more

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Cited by 53 publications
(18 citation statements)
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“…The proposed method is able to recognize most of the characters of the degraded or blurred document. The performance of proposed method is compare with bilateral filtering with binarization method and it has been found the proposed method work well is adverse condition even when background is highly contrast [14], [15]. Along with better image enhancement we are also able to extract the most of data written on such degraded documents in Sanskrit.…”
Section: Results Analysismentioning
confidence: 91%
“…The proposed method is able to recognize most of the characters of the degraded or blurred document. The performance of proposed method is compare with bilateral filtering with binarization method and it has been found the proposed method work well is adverse condition even when background is highly contrast [14], [15]. Along with better image enhancement we are also able to extract the most of data written on such degraded documents in Sanskrit.…”
Section: Results Analysismentioning
confidence: 91%
“…The NLM filter [3] is used as regularization prior with iterative image reconstruction methods. Using NLM for image restoration (denoising and super-resolution) was presented in [4], [11], [12], and in [5], [9] for image deblurring.…”
Section: Related Workmentioning
confidence: 99%
“…Indeed, documents suffering from bleed-through have their readability greatly decreased. Moreover, it results in a high OCR error rate [6]. For these reasons, research has been done to measure this defect in order to predict OCR error rates [7], and other works are able to restore degraded documents [8], [2], [9].…”
Section: Introductionmentioning
confidence: 99%