title: Deblur image with text to be recognized by OCR
body: <p>I have an image that is blurred:<br />
  <img src="https://i.stack.imgur.com/gAQlO.png" alt="1" />
  This is a part of the business card and it is one of the frames taken by the camera and without proper focus.</p>
  <p>The clear image looks like this
  <img src="https://i.stack.imgur.com/Kp124.png" alt="2" />
  I'm looking for a method that could give me an image of better quality, so that image could be recognized by OCR, but also should be quite fast. The image is not blurred too much (I think so) but isn't good for OCR. I tried:</p>
  <ul>
  <li>different kinds of HPF,</li>
  <li>Laplacian,</li>
  <li>Canny detector,</li>
  <li>combinations of morphological operations (opening, closing).</li>
  </ul>
  <p>I also tried:</p>
  <ul>
  <li>deconvolution with Wiener filter,</li>
  <li>deconvolution and the Lucy-Richardson method.</li>
  </ul>
  <p>But it was not easy to find the right PSF (Point Spread Function). These methods are considered effective, but not so fast enough. I also tried FFT and then IFFT with a Gaussian mask, but the results were not satisfactory. I'm looking for some kind of general method of deblurring images with text, not only this image. Could someone help me with this problem? I'll be grateful for any advice. I'm working with OpenCV 3 (C++ and sometimes Python).</p>