A new SAR image despeckling using correlation based fusion and method noise thresholding

Singh, Prabhishek; Shree, Raj; Diwakar, Manoj

doi:10.1016/j.jksuci.2018.03.009

Cited by 22 publications

(23 citation statements)

References 61 publications

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“…This detailed comparison is performed on some prevalent methods. 1,3,4,29,31,34,38,39,46,54,[62][63][64][65][66][67]…”

Section: Comparative Analysis Of Sar Image Despeckling Methodsmentioning

confidence: 99%

“…Figures 5 and 6 show the despeckling result of some of efficient latest nontraditional methods. 1,3,4,29,31,34,38,39,46,54 This comparison is made based on the visual quality of despeckling results and different metrics used for the performance analysis of these methods. The speckled SAR images taken for reference for the despeckling demonstration are shown in Figs.…”

Section: Qualitative and Quantitative Comparative Analysismentioning

confidence: 99%

“…54 Fig. 6 Despeckling results (a) 2018, 1 (b) 2020, 3 (c) 2021, 4 (d) 2022, 29 (e) 2022, 31 (f) 2022, 34 (g) 2021, 38 (h) 2021, 39 (i) 2021, 46 and (j) 2019. 54 Singh, Shankar, and Diwakar: Review on nontraditional perspectives of synthetic aperture radar image.…”

Section: Contourlet Cnnmentioning

confidence: 99%

“…The methods 31,34,38 shows satisfactory result in terms of speckle reduction. Based on MSE values in Table 2, it can be said that 4,31 3,4,31 presents the best results due to higher values. Rest of other method ENL values are satisfactory.…”

Section: Contourlet Cnnmentioning

confidence: 99%

“…These high-frequency radar waves hit the target and reflect. 4 The backscattered energy is received by the SAR and processed as well. This processing of received SAR data requires a lot of time, as it is a high computational process.…”

Section: Introductionmentioning

confidence: 99%

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Review on nontraditional perspectives of synthetic aperture radar image despeckling

2022

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Synthetic aperture radar (SAR) image despeckling is a preprocessing method. SAR images are, by default, noisy in nature. The kind of noise found in SAR images is called speckle noise. The effect of this noise on SAR images is highly adverse. It degrades the quality of the SAR image, resulting in the loss of vital information. Since SAR images are inherently speckled in nature, it costs a lot of information loss. The removal of such noise from the SAR image is mandatory and is the first step. The elimination of speckle noise from SAR images is called SAR image despeckling. There are various traditional and nontraditional methods of SAR image despeckling based on Bayesian and non-Bayesian techniques. The SAR image despeckling methods based on Bayesian techniques are further subdivided into spatial and transform domains. This paper presents a comparative review of nontraditional perspectives on SAR image despeckling. The comparison is made based on methodology, objectives, merits, and demerits. Its focus is to do analysis of all the latest research done in the field of SAR image despeckling using nontraditional methods.

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“…This detailed comparison is performed on some prevalent methods. 1,3,4,29,31,34,38,39,46,54,[62][63][64][65][66][67]…”

Section: Comparative Analysis Of Sar Image Despeckling Methodsmentioning

confidence: 99%

Section: Qualitative and Quantitative Comparative Analysismentioning

confidence: 99%

Section: Contourlet Cnnmentioning

confidence: 99%

Section: Contourlet Cnnmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Review on nontraditional perspectives of synthetic aperture radar image despeckling

2022

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Total variation‐based ultrasound image despeckling using method noise thresholding in non‐subsampled contourlet transform

Singh

Diwakar

2023

Int J Imaging Syst Tech

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Medical diagnostics rely heavily on ultrasound imaging since it is non-invasive, inexpensive, and able to provide images in real time. However, the inherent existence of a kind of signal-dependent noise in these images diminishes the use of ultrasound imaging systems. Speckle noise is inherently present in ultrasound images. Its inherent presence occurs during the image acquisition phase. It decreases the diagnostic usefulness of this imaging modality since it interferes with and reduces the image resolution and contrast. Speckle noise is multiplicative in nature. This multiplicative nature of speckle noise causes adverse effects on ultrasound imaging because it distorts the image quality and causes a loss of the patient's informative content in ultrasound imaging. This causes difficulty in tissue characterization. A lot of research has been done in this field to remove speckle noise while preserving medical information in the image. To handle this issue, research has been grouped into multiple domains. The two main domains include homomorphic and non-homomorphic filtering. The homomorphic filtering uses a logarithmic transform that converts this multiplicative nature into an additive nature and uses any additive image restoration model to do a despeckling task. Non-homomorphic filtering encompasses all methods that do not employ a logarithmic transform. Since the presence of speckle noise in ultrasound imaging is an inherent property. Therefore, the despeckling of medical ultrasound images is a mandatory task that cannot be avoided or ignored. This paper proposes a two-step hybrid and homomorphic despeckling technique, where modified total variation method is applied as step one for speckle reduction purposes. Step two implements method of noise thresholding in the non-subsampled contourlet transform (NSCT) domain using the bivariate shrinkage rule for edge preservation. The effectiveness and reliability of the proposed method are tested by comparing it with some of the latest methods based on qualitative and quantitative analyses. This paper will help the new researchers understand various problems and their solutions related to ultrasound image despeckling.

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MSPB: intelligent SAR despeckling using wavelet thresholding and bilateral filter for big visual radar data restoration and provisioning quality of experience in real-time remote sensing

Singh

Shankar

Diwakar

et al. 2022

Environ Dev Sustain

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A new SAR image despeckling using correlation based fusion and method noise thresholding

Cited by 22 publications

References 61 publications

Review on nontraditional perspectives of synthetic aperture radar image despeckling

Review on nontraditional perspectives of synthetic aperture radar image despeckling

Total variation‐based ultrasound image despeckling using method noise thresholding in non‐subsampled contourlet transform

MSPB: intelligent SAR despeckling using wavelet thresholding and bilateral filter for big visual radar data restoration and provisioning quality of experience in real-time remote sensing

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