Wavelet Based Image Denoising with Mixed Laplace Model
عنوان مقاله: Wavelet Based Image Denoising with Mixed Laplace Model
شناسه ملی مقاله: ACCSI11_208
منتشر شده در یازدهمین کنفرانس سالانه انجمن کامپیوتر ایران در سال 1384
شناسه ملی مقاله: ACCSI11_208
منتشر شده در یازدهمین کنفرانس سالانه انجمن کامپیوتر ایران در سال 1384
مشخصات نویسندگان مقاله:
Hossein Rabbani - PhD Student Biomedical Engineering Dept. Amirkabir Univ. of Technology
Mansur Vafadoost - Assistant Professor Biomedical Engineering Dept.Amirkabir Univ. of Technology
خلاصه مقاله:
Hossein Rabbani - PhD Student Biomedical Engineering Dept. Amirkabir Univ. of Technology
Mansur Vafadoost - Assistant Professor Biomedical Engineering Dept.Amirkabir Univ. of Technology
The performance of various estimators, such as maximum a posteriori (MAP) is strongly dependent on correctness of the proposed model of noise-free data distribution. Therefore, the selection of a proper model for wavelet coefficients distribution is very important in the wavelet based image denoising. This paper presents a new image denoising algorithm based on the modeling of wavelet coefficients in each subband with a mixture of Laplace random variables (rvs). Indeed, we design a MAP estimator, which relies on the mixture distributions. Using this relatively new statistical model we are able to better capture the heavy-tailed nature of wavelet coefficients. The simulation results show that our proposed method yields better performance than several published methods visually and quantitatively.
کلمات کلیدی: MAP estimator, mixture model, wavelet transform
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/127297/