Brief overview and software implementation of selected methods for deconvolution of images
Abstract
Brief overview and software implementation of selected methods for deconvolution of images
Incoming article date: 14.11.2017In this article, we briefly reviewed the problem of image quality loss. Methods for restoring defocused images are considered and analyzed. Describes lubrication functions and ways of defocusing the image, as well as a mechanism for eliminating the three main types of image blurring. A number of experiments were conducted on the defocused images. An algorithm for deconvolving an image using a Wiener filter and using the Tikhonov regularization method is disassembled. The analysis of the efficiency of the Wiener filter and Tikhonov regularization for blurred images is performed. The comparative analysis was carried out using the developed software for the restoration of defocused images in the Microsoft Visual Studio 2012 environment. For the Fourier transform, the library was used - aForge. A certain dependence of the execution time of the algorithm on the size of the image to be reconstructed. It is established that on the tested problems - the time complexity of the Wiener filter is 1.1 times less than the time complexity of Tikhonov regularization.
Keywords: Wiener filter, Wiener deconvolution, Tikhonov regularization, image reconstruction, blurred images, motion blur, Gaussian blur