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Image Denoising Using Mathematical Tools / by Mourad Talbi, Brahim Nasraoui.

Springer Nature - Synthesis Collection of Technology (R0) eBook Collection 2026 Available online

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Format:
Book
Author/Creator:
Talbi, Mourad.
Series:
Synthesis Lectures on Engineering, Science, and Technology, 2690-0327
Language:
English
Subjects (All):
Signal processing.
Telecommunication.
Computer networks.
Signal, Speech and Image Processing.
Communications Engineering, Networks.
Computer Communication Networks.
Local Subjects:
Signal, Speech and Image Processing.
Communications Engineering, Networks.
Computer Communication Networks.
Physical Description:
1 online resource (83 pages)
Edition:
1st ed. 2026.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
Summary:
This book introduces and analyzes image denoising techniques. In the first chapter, the authors detail image denoising approaches employing Adaptive Frequency Median Filter (AFMF). In the second chapter, the authors present the first image denoising technique based on two different wavelet transforms, which are 2-D dual-tree DWT and Stationary Wavelet Transform 2-D. In the third chapter, the authors discuss the MRI Denoising based on 2-D Dual-Tree DWT and Stationary Wavelet Transform 2-D. Covers image denoising techniques with tools such as wavelet transforms and Adaptive Frequency Median Filter (AFMF); Discusses and combines Stationary Wavelet Transform 2-D and 2-D Dual-Tree DWT; Presents MRI Denoising using AFMF techniques. .
Contents:
Introduction
Adaptive Frequency Median Filter (AFMF)
An Image Denoising Technique based on 2-D dual-tree DWT and Stationary Wavelet Transform 2-D
2D Dual-Tree Complex Wavelet Transform
A SWT-Based Image Denoising Technique
The Proposed Image Denoising Technique
Weakness of the proposed image denoising technique
Real-Time Implementation of the Proposed Image Denoising Approach
2-D Stationary Wavelet Transform and 2-D Dual-Tree DWT for MRI Denoising
A ๐‘†๐‘Š๐‘‡ 2-๐ท based Image Denoising Approach
Conclusion.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
3-032-11878-6
9783032118783
OCLC:
1565878398

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