Deblurring X-Ray Digital Image Using LRA Algorithm
Ashwan Anwer Abdulmunem, Ahmed K. Hassan · Journal of Physics Conference Series · 2019
Abstract Deblurring of X-rays digital images has always been a problem of crucial interest. A specific solution to the problem of image restoration is generally determined by the nature of degradation phenomena. So, it is highly dependent on the nature of the noise present there. In this work Lucy Richardson algorithm (LRA) is implemented on the X-ray image and deblurring is processes is observed. Deblurring is an important step of image processing especially when the diagnosis needs to be classified based on the result of X-ray image. LRA is an iterative procedure in which the pixels of the observed image are represented using the PSF. Image restoration is an emerging field of image processing in which the focus is on recovering an original image from a degraded image. The blurred image can be a result of a known degradation or unknown degradation. Hence image deblurring can be defined as a process of recovering a sharp image from a degraded image which is blurred by a degradation function, commonly by a Point Spread Function (PSF). The Point Spread Function describes the response of an imaging system to a point source or point object.