Fusion Despeckling Based on Surface Variation Anisotropic Diffusion Filter and Ratio Image Filter

Feng, Guo; Guo, Zhang; Zhang, Qingjun; Zhao, Ruishan; Deng, Minghua; Kai, Xu; Jia, Peng; Hao, Xiaoyan

doi:10.1109/tgrs.2019.2948890

Cited by 10 publications

(3 citation statements)

References 36 publications

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“…where, N constant is a constant (can be ignored later). Taking the negative of (15), the data fidelity term can be obtained…”

Section: Data Fidelity Term Of Nlr Despeckling Modelmentioning

confidence: 99%

“…Nevertheless, it cannot protect the details well, which degrades the consequential despeckling performance. As reported in [12], [13], [14], [15], [16], some variational-based variant methods could yield satisfactory results in despeckling, but they are difficult to implement due to the heavy computation burden. Another typical method is the bilateral filter (BF) [17], which is widely used in denoising, sharpness enhancement, and upsampling.…”

Section: Introductionmentioning

confidence: 97%

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A Novel SAR Image Despeckling Method Based on Local Filter With Nonlocal Preprocessing

Wang

Guo

2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Owing to the characteristics of long distance and strong penetration, a synthetic aperture radar (SAR) imaging system could provide ground information with high resolution under a poor climate environment. Nevertheless, speckle is still a common interference of the output that deteriorates the content of SAR images and further affects the recognition of real objects. In this article, a new speckle suppression method is proposed from the perspective of exploring nonlocal and local SAR image features. Considering the statistical distribution of SAR images, a novel local filter termed SAR-orientated guided bilateral filter is proposed to characterize the range and spatial similarity of SAR images. Meanwhile, an optimized nonlocal filter based on the weight Schatten-p norm is introduced to characterize the nonlocal self-similarity of SAR images by a low-rank model. As a preprocessing step, it yields nonlocal filtering features as the guidance image of the proposed SAR-oriented guided bilateral filter. By incorporating the nonlocal filtering feature into the local filter, the structured method could achieve desirable despeckling results. Extensive experiments on real SAR images demonstrate that the proposed method outperforms several state-of-the-art methods in terms of both visual satisfaction and quantitative metrics.

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“…where, N constant is a constant (can be ignored later). Taking the negative of (15), the data fidelity term can be obtained…”

Section: Data Fidelity Term Of Nlr Despeckling Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

A Novel SAR Image Despeckling Method Based on Local Filter With Nonlocal Preprocessing

Wang

Guo

2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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show abstract

“…Multiple speckle denoising techniques have been proposed in the literature [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] which aims to restore speckle corrupted images. To begin with, a multiplicative noise filtering model was proposed in [20].…”

Section: Related Workmentioning

confidence: 99%

SAR image denoising based on multifractal feature analysis and TV regularisation

2020

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A new denoising technique is proposed in this study for synthetic aperture radar (SAR) images corrupted by speckle noise. The authors method extract informative features from a noisy speckled image, and then a denoised version of this image is estimated from the informative gradients, which are restricted to the features of this image. The technique of extracting features is designed on the framework of multifractal formalism followed by a reconstruction technique for the informative gradients based on the total variational (TV) regularisation framework. Experimental results demonstrate that the proposed approach is able to retain the finer details of the original image while removing noise. The superiority of the proposed approach is manifested qualitatively and quantitatively on comparing with state-of-the-art denoising techniques.

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Efficient brain tumour detection system by Cascaded Fully Convolutional Improved DenseNet with Attention-based Adaptive Swin Unet-derived segmentation strategy

Vinisha,

Boda

2024

Multimedia Systems

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Fusion Despeckling Based on Surface Variation Anisotropic Diffusion Filter and Ratio Image Filter

Cited by 10 publications

References 36 publications

A Novel SAR Image Despeckling Method Based on Local Filter With Nonlocal Preprocessing

A Novel SAR Image Despeckling Method Based on Local Filter With Nonlocal Preprocessing

SAR image denoising based on multifractal feature analysis and TV regularisation

Efficient brain tumour detection system by Cascaded Fully Convolutional Improved DenseNet with Attention-based Adaptive Swin Unet-derived segmentation strategy

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