An Adaptive Richardson-Lucy Algorithm for Medical Image Restoration

• Autorzy: Yaqoub Qunoot A. , Al-Ani Ayad A.

Identyfikatory

DOI

10.26636/jtit.2023.168222

• Języki publikacji: EN

Abstrakty

EN

Image restoration is the process of estimating the original image content from a degraded picture. In this paper, the Richardson-Lucy iterative algorithm was developed to improve the quality of degraded medical images. It has been assumed that medical images are exposed to two types of degradation. The first type is the blur function in the Gaussian form with different widths, i.e. σ = 1 , 2, and 3. The second type of degradation was assumed to be of the independent white Gaussian noise type with different signal-to-noise ratio values: SNR = 10, 50 , and 100. The results obtained from the adaptive filter are compared, quantitatively, with different conventional filters: inverse, Wiener, and constraint least square, by applying different measures, such as: power signal to noise ratio (PSNR), structural similarity index (SSID), and root mean square error (RMSE). The comparison showed that the adaptive recovery filter achieves better results.

Słowa kluczowe

EN

constraint least square filter; Gaussian blurring function; Gaussian noise function; inverse filter; non-blind deconvolution; point spread function; Richardson-Lucy algorithm; Wiener filter

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2023
• Tom: nr 1
• Strony: 66--77
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Yaqoub Qunoot A.

• College of Information Engineering, Al-Nahrain University, Baghdad, Iraq

autor

Al-Ani Ayad A.

• College of Information Engineering, Al-Nahrain University, Baghdad, Iraq

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).