نوع مقاله: مقاله کامل پژوهشی

نویسنده

استادیار، گروه فیزیک و مهندسی پزشکی، دانشکده پزشکی، دانشگاه علوم پزشکی اصفهان عضو هیئت علمی مرکز تحقیقات پردازش تصویر و سیگنال پزشکی

10.22041/ijbme.2009.13403

چکیده

در این مقاله چگونگی بهبود محوشدگی تصاویر اولتراسوند با استفاده از الگوریتمی تکراری مبتنی بر تخمین اولیه داده های تمیز و تابع محوشدگی بر اساس روش کمینه کردن گرادیان خطا (روش نیوتن) و ارتقاء کیفیت این تخمین ها با استفاده از روش های کاهش اغتشاش مناسب ارائه شده است. بر این اساس با تعریف تابع خطای مناسب، تخمین اولیه موجب حفظ لبه های تصویر می شود و سپس تخمین اولیه تابع محوشدگی بر اساس روش کاهش تطبیقی اغتشاش که برای هر پیکسل پنجره محلی و غیرهمسانگرد با شکل متناسب انتخاب می کند، بهبود می یابد. همچنین تخمین اولیه داده های تمیز با استفاده از روش کاهش اغتشاش مبتنی بر تئوری بیز در حوزه ویولت مختلط ارتقاء می یابد. استفاده از روش های کاهش اغتشاش مذکور مانع از ایجاد آرتیفکت های بصری در محل های هموار تصاویر و همچنین محوشدگی لبه های اصلی تصاویر می شود. نتایج شبیه سازی های صورت گرفته حاکی از موفقیت قابل توجه این روش در عملیات حذف محوشدگی در مقایسه با دیگر روش های ارائه شده در سال های اخیر دارد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Deblurring Of Ultrasonic Images Based On Iterative Gradient Algorithm, Anisotropic Window And Complex Wavelet-Based Denoising

نویسنده [English]

  • Hossein Rabbani

Assistant Professor, Department of Physics and Biomedical Engineering, School of Medicine, Isfahan Univ. of Medical Sciences Medical Image and Signal Processing Research Center

چکیده [English]

In this paper, ultrasonic images are initially deblurred using Gradient method and then the estimations of image and point spread function (PSF) are improved using denoising techniques. For this reason, at first a criterion with appropriate regularizers (that results in preservation of the edges) is defined for the iterative Gradient method, then the estimation of PSF is improved using a denoising technique based on using an anisotropic window around each pixel. The initial estimation of image is also improved using a denoising method in complex wavelet domain that proposes maximum a posteriori (MAP) estimator and local Laplacian prior density function. Using these denoising methods on top of Gradient method causes that our algorithm reduces the visual artifacts and preserves the edges in the deblurred images. Our simulations show that the proposed method in this paper outperforms other methods visually and quantitatively.

کلیدواژه‌ها [English]

  • Ultrasonic Images
  • Blurring
  • Gradient Algorithm
  • Denoising
  • Video Processing
  • Blind Deconvolution

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