A real time adaptive multiresolution adaptive Wiener filter based on adaptive neuro-fuzzy inference system and fuzzy evaluation
سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 212
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شناسه ملی سند علمی:
JR_IJNAA-12-1_002
تاریخ نمایه سازی: 11 آذر 1401
چکیده مقاله:
In this paper, a real-time denoising filter based on modelling of stable hybrid models is presented. The hybrid models are composed of the shearlet filter and the adaptive Wiener filter in different forms. The optimization of various models is accomplished by the genetic algorithm. Next, regarding the significant relationship between Optimal models and input images, changing the structure of Optimal models for image denoising is modelled by the ANFIS. The eight hundred digital images are used as train images. For eight hundred training images, Sixty seven models are found. For integrated evaluation, the amounts of image attributes such as Peak Signal to Noise Ratio, Signal to Noise Ratio, Structural Similarity Index, Mean Absolute Error and Image Quality Assessment are evaluated by the Fuzzy deduction system. Finally, for the features of a sample noisy image as test data, the proposed denoising model of ANFIS is compared with wavelet filter in ۲ and ۴ level , Fast bilateral filter, TV-L۱, Median, shearlet filter and the adaptive Wiener filter. In addition, run time of proposed method are evaluated. Experiments show that the proposed method has better performance than others.
کلیدواژه ها:
Genetic algorithm ، denoising ، Fuzzy deduction system ، Image processing ، wavelet transformation ، adaptive bilateral filters ، adaptive neuro-fuzzy inference system
نویسندگان
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Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran.
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Department of Mathematics, Iran University of Science and Technology, Tehran ۱۶۸۴۶۱۳۱۱۴, Iran. Department of Mathematical Sciences, University of South Africa, Pretoria ۰۰۰۲, South Africa.
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Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran.