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## Deblurring revisited with Wiener filter using OpenCV
In this post I continue to experiment with the de-blurring of images using the Wiener filter. The Wiener filter attempts to de-blur by assuming that the source signal is convolved with a blur kernel in the presence of noise. I am including the de-blurring with 3 different blur kernel radii and different values for the Wiener constant K. While the de-blurring is still a long way off there is some success. One of the reasons I have assumed a non-blind blur kernel and try to de-convolve with that. The Wiener filter tries to minimize the Mean... [More]
Tags: wiener deblurring opencv filter |

## Computer Vision:Ramblings on derivatives, contours and histograms
Images can be visualized to be functions of the form f(x,y) where f(x,y) represents the intensity at the pixel position ,y. However images can be grayscale, color or four channels and each channel may consist of integers or floating point numbers. However the changes in the values can be viewed as a continuous function. Here is a nice representation of an image as a continuous function (courtesy: Prof Darrell’s lecture at Berkeley on Filters) Given that the image can be viewed as a continuous function in 2 or 3 axes we have derivatives that... [More]
Tags: filter histograms contours sobel canny laplacian |

## Dabbling with Weiner filter using OpenCV
The technique of reduction of blur and restoration of images is an extremely important field of study and finds numerous applications in medical imaging and astronomy. One such technique is Wiener filter named after the originator of the technique Prof. Norbert Wiener (1894-1964). It is usually important to consider these techniques in the frequency domain. This can be represented diagrammatically as follows Given that we have b(x,y) = i(x,y) * k(x,y) + n(x,y) – (1) where b(x,y) is the blurred image,... [More]
Tags: dft weiner inverse-dft filter opencv |