'Mechanical Engineering Faculty in Slavonski Brod'
Doi
Abstract
Predlažemo ponderirani stupnjevani filtar za otklanjanje Poissonova šuma na rendgenskim slikama. U unaprijed definiranom prozoru izračunat je gradijent središnjeg piksela. Za izračunavanje vrijednosti gradijenta primijenjen je Gaussov ponderirani filtar. Predložena metoda je primijenjena na biomedicinske rendgenske slike, a zatim na različite uobičajene slike LENE i paprika. Rezultati pokazuju učinkovitost i bolju jasnoću slika uz primjenu ponderiranog stupnjevanog filtra. Uz to, predložena metoda je računalno vrlo učinkovita i brža od Non Local Mean (NLM) filtra koji predstavlja unaprijeđenu metodu za otklanjanje Poissonova šuma. Rezultati predložene metode su također bolji u odnosu na parametre za mjerenje performanse t.j. korelacije, Peak Signal-to-Noise Ratio (PSNR), Maximum Structural Similarity Index Measure (MSSIM) i Mean Square Error (MSE) nego uobičajeni Median, Wiener i NLM filter.We propose a Weighted Gradient Filter for denoising of Poisson noise in medical images. In a predefined window, gradient of the centre pixel is averaged out. Gaussian Weighted filter is used on all calculated gradient values. Proposed method is applied on biomedical images X-Rays and then on different general images of LENA and Peppers. Recovery results show that the proposed weighted gradient filter is efficient and has better visual appearance. Moreover, proposed method is computationally very efficient and faster than Non Local Mean (NLM) filter which is an advanced technique for Poisson noise removal. Proposed method results are also better in terms of performance measures parameters i.e. correlation, Peak Signal-to-Noise Ratio (PSNR), Maximum Structural Similarity Index Measure (MSSIM) and Mean Square Error (MSE) than the conventional Median, Wiener and NLM filter
