Answers.Body: <p>This is also the topic of Image Processing (which has analytical solutions instead of learning) mostly through predesigned filters. The filter depends on the type of noise, (salt &amp; pepper, Gaussian, etc.) i.e., for salt &amp; pepper choosing the median in a window. There are a lot of denoising research in literature. There are also more recent learning based denoising applications, but it requires data so that you can train.</p>
  
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Answers.CreationDate: 2019-01-24T08:38:26.740Z
Answers.Text: thank you for you clarification, Do you recall any articles or links to start with? 
  It is OK for the data, I can provide data for training and testing.
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Answers.CreationDate: 2019-01-24T09:58:54.637Z
Answers.Text: This seems as a good article: http://papers.nips.cc/paper/4686-image-denoising-and-inpainting-with-deep-neural-networks  . Also, inpainting might be needed if occlusions are too much. If you want analytic solutions, you can also look up sparse representations/dictionary learning methods for denoising/inpainting.
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Answers.CreationDate: 2019-01-24T11:25:25.133Z
Answers.Text: Also, I forgot to mention, but if you specifically target documents, then you can narrow down your research. Some lookup returned these that look promising: Kaggle competition on what you ask. https://www.kaggle.com/c/denoising-dirty-documents , A paper on removing corruption in scanned documents. https://unitec.researchbank.ac.nz/handle/10652/2730
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Answers.Text: The Kaggle competion sounds promising, thank you for the sources!
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Body: <p>I have some documents containing some text (machine writing text) that I intend to apply OCR on them in order to extract the text.</p>
  <p>The problem is that these documents contain a lot of noise but in different ways (some documents have noise in the middle, others in the top, etc.), which means that I can't apply simple thresholding in order to remove the noise (i.e applying simple threshold does not only remove the noise, but it removes some parts of the text).</p>
  <p>For these reasons, I thought about using AI to de-noise the documents.</p>
  <p>Does anyone know if it is possible to do that with AI or any alternative way?</p>
  
Tags: <machine-learning><reference-request><optical-character-recognition>
Title: Is it possible to use AI to denoise noisy documents?
UserDisplayName: singrium
ThreadText: # Is it possible to use AI to denoise noisy documents?
  
  (Asked by: username_0 on 2019-01-23)
  
  I have some documents containing some text (machine writing text) that I intend to apply OCR on them in order to extract the text.
  
  The problem is that these documents contain a lot of noise but in different ways (some documents have noise in the middle, others in the top, etc.), which means that I can't apply simple thresholding in order to remove the noise (i.e applying simple threshold does not only remove the noise, but it removes some parts of the text).
  
  For these reasons, I thought about using AI to de-noise the documents.
  
  Does anyone know if it is possible to do that with AI or any alternative way?
  
  **Tags:** machine-learning, reference-request, optical-character-recognition
  
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  ## 1 answers
  
  ### Answer by username_1 on 2019-01-23. Score: 4
  
  This is also the topic of Image Processing (which has analytical solutions instead of learning) mostly through predesigned filters. The filter depends on the type of noise, (salt & pepper, Gaussian, etc.) i.e., for salt & pepper choosing the median in a window. There are a lot of denoising research in literature. There are also more recent learning based denoising applications, but it requires data so that you can train.
  
  > **Comments:**
  > **username_0**: thank you for you clarification, Do you recall any articles or links to start with?  It is OK for the data, I can provide data for training and testing.  
  > **username_1**: This seems as a good article: http://papers.nips.cc/paper/4686-image-denoising-and-inpainting-with-deep-neural-networks  . Also, inpainting might be needed if occlusions are too much. If you want analytic solutions, you can also look up sparse representations/dictionary learning methods for denoising/inpainting.  
  > **username_1**: Also, I forgot to mention, but if you specifically target documents, then you can narrow down your research. Some lookup returned these that look promising: Kaggle competition on what you ask. https://www.kaggle.com/c/denoising-dirty-documents , A paper on removing corruption in scanned documents. https://unitec.researchbank.ac.nz/handle/10652/2730  
  > **username_0**: The Kaggle competion sounds promising, thank you for the sources!  
  
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