Fast Deblurring Method for Computed Tomography Medical Images Using a Novel Kernels Set
The fastest way to deblur an image is by convolving a special kernel to the corrupted image. Laplacian kernels are famous and widely used in this field, but the issue is only few kernels are presented. This work attempts to recover the degraded images by using twenty novel kernels. Moreover, these kernels were tested with five types of blur that are: Average, Box, Gaussian, Pillbox and Atmospheric turbulence blur to determine which type of blur is suitable to be employed with kernels the most.
this work is related to the following article:
Al-Ameen, Z., Sulong, G., and Johar, M. G. M. (2012). Fast deblurring method for computed tomography medical images using a novel kernels set. International Journal of Bio-Science and Bio-Technology, 4(3), 9-20.
Please cite the above article if you use its code.
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Zohair Al-Ameen (2024). Fast Deblurring Method for Computed Tomography Medical Images Using a Novel Kernels Set (https://www.mathworks.com/matlabcentral/fileexchange/48671-fast-deblurring-method-for-computed-tomography-medical-images-using-a-novel-kernels-set), MATLAB Central File Exchange. Récupéré le .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Filtering and Enhancement > Deblurring >
- Sciences > Physics > Medical Physics >
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