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Image restoration in digital radiography using dual sensor Wiener filter
Author(s) -
Lee Tae Soo,
Min Byoung Goo
Publication year - 1991
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.596621
Subject(s) - wiener filter , filter (signal processing) , image quality , digital radiography , computer vision , image sensor , computer science , signal to noise ratio (imaging) , wiener deconvolution , computed radiography , noise (video) , artificial intelligence , radiography , mathematics , algorithm , image (mathematics) , physics , telecommunications , blind deconvolution , nuclear physics , deconvolution
A dual sensor Wiener filter (DSWF) technique was used to improve the image quality of a scanning type digital radiographic system. In a digital radiographic system, image quality is evaluated by resolution and SNR (signal‐to‐noise ratio), which are two important parameters representing the objective performance of the system. In this method, when two images are acquired in the same region using two sensors with different characteristics of resolution and SNR, they are processed simultaneously using DSWF, which is the extended concept of a Wiener filter to two dimensions. DSWF uses the cross power spectrum between dual sensor outputs of the same chest radiographic image in the design of filter parameters. It has been implemented with fast algorithm using FFT (fast Fourier transform). The performance of the proposed method is compared with that of conventional methods (Wiener filter and parametric projection filter). In simulation studies, it is shown in 12 cases that this new method has SNR improvement of 1–2 dB better than conventional methods.