A Nonlocal TV-Based Variational Method for PolSAR Data Speckle Reduction

Nie, Xiangli; Qiao, Hong; Zhang, Bo; Huang, Xiayuan

doi:10.1109/tip.2016.2552402

Cited by 49 publications

(28 citation statements)

References 43 publications

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“…ormance of the filter results can be quantitatively evaluated according to image. As mentioned in [35,40], the preservation of the polarimetric and alyzed, and the evaluation of the suppression was measured. Specifically, of the pixel were denoted by the complex correlation parameters (Ca, eter was corresponding to the power information (P).…”

Section: Datamentioning

confidence: 99%

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Feature-Based Nonlocal Polarimetric SAR Filtering

et al. 2017

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Polarimetric synthetic aperture radar (PolSAR) images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance (CV) and Pauli basis (PB) to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

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Section: Datamentioning

confidence: 99%

“…The value edge preservation. The equivalent number of looks (ENL) was applied to ression, which was defined as the square ratio of the mean to the standard geneous region [40][41][42]. The larger the ENL was, the better the quality of .…”

Section: Datamentioning

confidence: 99%

Feature-Based Nonlocal Polarimetric SAR Filtering

et al. 2017

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“…Direct formulation of the objective function on the full covariance matrices raises several problems: (i) computational complexity due to the nonconvexity of the data-fitting term; (ii) difficulty to express regularity properties of the complex-valued terms of the covariance matrices; (iii) non-stationary variance of speckle that leads to over/under-smoothing in some areas. These difficulties explain that very few works were conducted in this direction, with the exception of recent works on multi-channel TV regularizations [52], [53], [54]. Finally, while the homomorphic transform approach is well understood on intensity images, no variance stabilization transform is known for multi-channel images.…”

Section: Introductionmentioning

confidence: 99%

MuLoG, or How to Apply Gaussian Denoisers to Multi-Channel SAR Speckle Reduction?

Deledalle

Denis

Tabti

et al. 2017

IEEE Trans. on Image Process.

129

100

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Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric, or tomographic modes, SAR images are multi-channel and speckle reduction techniques must jointly process all channels to recover polarimetric and interferometric information. The distinctive nature of SAR signal (complex-valued, corrupted by multiplicative fluctuations) calls for the development of specialized methods for speckle reduction. Image denoising is a very active topic in image processing with a wide variety of approaches and many denoising algorithms available, almost always designed for additive Gaussian noise suppression. This paper proposes a general scheme, called MuLoG (MUlti-channel LOgarithm with Gaussian denoising), to include such Gaussian denoisers within a multi-channel SAR speckle reduction technique. A new family of speckle reduction algorithms can thus be obtained, benefiting from the ongoing progress in Gaussian denoising, and offering several speckle reduction results often displaying method-specific artifacts that can be dismissed by comparison between results.

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“…During a plenty of times, many approaches for the purpose have been discovered in scientific literature. However, the image smoothing problems significantly come into the notice are reported in many research articles including local filtering-based image smoothing [1,2], nonlocal-based methods [3][4][5][6] are also noted in literature. Nonlocal wavelet-based method [7,8], nonlocal-based sparse coding strategy [9], nonlocal lowrank [10], the sparse representation techniques [11], shearlet-based model [12], curvelet-based method [13], dictionary-based approaches [14,15], soft-thresholding method [16], image deblurring technique using regularization [17], the radial basis function (RBF)-based method [18] and image retrieval with color and angle representation [19] are also remarkable in applications.…”

Section: Introductionmentioning

confidence: 99%

A Robust Functional Minimization Technique to Protect Image Details from Disturbances

Islam¹,

Xu²,

Han³

et al. 2019

IJITCS

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Image capturing using faulty systems or environmental vulnerabilities always degrade the image quality and causes the distortion of true details from the original imaging signals. Thus a robust way of image enhancement and edge preservation is an enormously requirement for smooth imaging operations. Although, many techniques have been deployed in this area during the decades for its betterment. However, the key challenges are remain towards better tradeoff between image enhancement and details protection. Therefore, this study inspects the existing limitations and proposes a robust technique based on functional minimization scheme in variational framework for ensuring better performance in case of image enhancement and details preservation simultaneously. A vigorous way to solve the minimization problem is also develop to make sure the efficiency of the proposed technique than some other traditional techniques.

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A Nonlocal TV-Based Variational Method for PolSAR Data Speckle Reduction

Cited by 49 publications

References 43 publications

Feature-Based Nonlocal Polarimetric SAR Filtering

Feature-Based Nonlocal Polarimetric SAR Filtering

MuLoG, or How to Apply Gaussian Denoisers to Multi-Channel SAR Speckle Reduction?

A Robust Functional Minimization Technique to Protect Image Details from Disturbances

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