A new homomorphic and method noise thresholding based despeckling of SAR image using anisotropic diffusion

This article introduces the concept, use and implementation of method noise in the field of synthetic aperture radar (SAR) image despeckling. Method noise has the capability to enhance the efficiency and performance of any despeckling algorithm. It is easy, efficient and enhanced way of improving the results. The difference between speckled image and despeckled image contains some residual image information which is due to the inefficiency of the denoising algorithm. This article will compare the results of some standard methods with and without the use of method noise and prove its efficiency and validity. It also shows its best use in different ways of denoising. The results will be compared on the basis of performance metrics like PSNR and SSIM. The concept of method noise is not restricted to only SAR images. It has vast usage and application. It can be used in any denoising procedure such as medical images, optical image etc. but this paper shows the experimental results only on the SAR images.

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Algorithm for reducing speckle noise in SAR image by anisotropic diffusion

JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENT ◽

10.3724/sp.j.1187.2011.00857 ◽

2011 ◽

Vol 25 (10) ◽

pp. 857-863 ◽

Cited By ~ 1

Author(s):

Lei Zhu ◽

Dong Cheng

Keyword(s):

Anisotropic Diffusion ◽

Speckle Noise ◽

Sar Image

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Wavelet-based Multi-focus Image Fusion using Average Method Noise Diffusion (AMND)

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200720163938 ◽

2020 ◽

Vol 13 ◽

Cited By ~ 2

Author(s):

Prabhishek Singh ◽

Manoj Diwakar

Keyword(s):

Image Fusion ◽

Average Method ◽

Anisotropic Diffusion ◽

Visual Sensor ◽

Edge Preservation ◽

Fusion Technique ◽

Visual Appearance ◽

Method Noise ◽

Focus Image ◽

Image Fusion Technique

Aim: This paper presents a new and upgraded wavelet-based multi-focus image fusion technique using average method noise diffusion (AMND). Objective: Improved visual appearance of the final image, no blurring in the final fused image and clearly visible objects (fine edges). Methods: This method extends the standard wavelet-based image fusion technique on multi-focus images by incorporating the hybrid of method noise and anisotropic diffusion in it. This hybrid structure of method noise and anisotropic diffusion is implemented as the post-processing operation in the proposed method. Results: The proposed work shows excellent results in terms of visual appearance and edge preservation. The experimental results of the proposed method are compared with some of the traditional and non-traditional approaches where the proposed method shows comparatively better results. Conclusion: This paper depicts the robustness, effectiveness and adaptive nature of method noise in the field of image enhancement especially in the field of image fusion. The performance of the proposed method is analyzed qualitatively (good visual appearance) and quantitatively (entropy, spatial frequency, and standard deviation). This method has the capability to be incorporated in real-time applications like surveillance in the visual sensor network (VSN).

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A new SAR image despeckling using directional smoothing filter and method noise thresholding

Engineering Science and Technology an International Journal ◽

10.1016/j.jestch.2018.05.009 ◽

2018 ◽

Vol 21 (4) ◽

pp. 589-610 ◽

Cited By ~ 14

Author(s):

Prabhishek Singh ◽

Raj Shree

Keyword(s):

Sar Image ◽

Smoothing Filter ◽

Method Noise ◽

Image Despeckling

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The Comparison of Isotropic and Anisotropic Diffusion Techniques for Image Denoising

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.34-35.557 ◽

2010 ◽

Vol 34-35 ◽

pp. 557-561

Author(s):

Cui Yin Liu ◽

Chun Yu Zhang ◽

Hong Zhao Yuan ◽

Xi Long Qu

Keyword(s):

Diffusion Process ◽

Nonlinear Diffusion ◽

Anisotropic Diffusion ◽

Diffusion Processes ◽

Local Information ◽

Linear Diffusion ◽

Anisotropic Conductivity ◽

Method Noise ◽

Non Linear ◽

The Difference

The non-linear diffusion techniques were proposed for overcome the linear diffusion defaults. The linear diffusion was a homogeneous diffusivity with a constant conductivity. In this diffusion process, the noise and the edges were smoothed in the image. In order to prevent the edge from being smoothed during the denoising, the nonlinear diffusion was proposed by Pereona and Malik. In this method, noise was smoothed Simultaneously with the edges blurred. In diffusion processes, the conductivity is dependent on the image local information. We analyzed the ineffectiveness of isotropic and extended the work into the tensor-based anisotropic diffusion. It would be desirable to rotate the flux towards the orientation of interesting features. We compare the difference of isotroic linear and non-linear anisotropic diffusivity, and considere how to design non-linear anisotropic conductivity based on the different requires of the image filtering.

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