Wavelet based speckle reduction with application to SAR based ATD/R

Guo, Haitao; Odegard, J.E.; Lang, Markus; Gopinath, R.; Selesnick, Ivan; Burrus, C.S.

doi:10.1109/icip.1994.413278

Cited by 166 publications

(104 citation statements)

References 9 publications

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“…[11]- [15].But there are some draw backs of using those thresholds as shown in [16]. Thus we are using brute force thresholding which gives best results as compared to above threshold techniques.…”

Section: Introductionmentioning

confidence: 99%

Speckle Reduction of Synthetic Aperture Radar Images using Median Filter and Savitzky-Golay Filter

Gir¹,

Jain²,

Rai³

2015

IJCA

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SAR images are corrupted by speckle noise which is based on multiplicative noise or Reyleigh noise. The speckle degrades the quality of image and makes interpretations, analysis and classifications of SAR images harder. Therefore some speckle mitigation is necessary prior to the processing of SAR images. In this paper a new method is proposed for despeckling of SAR images in which Savitzky-Golay filter and median filter are used for denoising of the synthetic aperature radar (SAR) image. After obtaining filtered image they are decomposed by the use of undecimated wavelet transform. The speckled input image is also decomposed using undecimated wavelet transform. Then image segmentation is done by the use of brute force thresholding wavelet based algorithm in which each pixel of the entire decomposed image is compared and the maximum value of threshold image pixel is replaced in every iteration of image processing. Lastly enhanced directional smoothing of the image is done to obtain a despeckled image General TermsUndecimated Wavelet Transform, SAR, Savitzky-Golay filter, median filter, direction dependent mask, Directional Smoothing.

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Section: Introductionmentioning

confidence: 99%

Speckle Reduction of Synthetic Aperture Radar Images using Median Filter and Savitzky-Golay Filter

Gir¹,

Jain²,

Rai³

2015

IJCA

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“…To overcome some of these limitations, wavelet-based methods are often utilized [12], [13], [14], [15], [16], [17] in which noise shrinkage is applied to the detail wavelet coefficients of the noisy image [18], [19]. Since speckle is multiplicative in nature, some of these methods often apply logarithm transform to SAR images to convert the multiplicative noise into additive noise.…”

Section: Introductionmentioning

confidence: 99%

Separated Component-Based Restoration of Speckled SAR Images

Patel

Easley²,

Chellappa

et al. 2014

IEEE Trans. Geosci. Remote Sensing

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Abstract-Many coherent imaging modalities such as Synthetic Aperture Radar (SAR) suffer from a multiplicative noise commonly referred to as speckle which often makes the interpretation of data difficult. An effective strategy for speckle reduction is to use a dictionary that can sparsely represent the features in the speckled image. However, such approaches fail to capture important salient features such as texture. In this paper, we present a speckle reduction algorithm that handles this issue by formulating the restoration problem so that the structure and texture components can be separately estimated with different dictionaries. To solve this formulation an iterative algorithm based on surrogate functionals is proposed. Experiments indicate the proposed method performs favorably compared to state-ofthe-art speckle reduction methods.

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“…As a first step of our approach (see Figure 1), and similarly to existing techniques [1,2,4], the logarithm of the image is decomposed into several scales through a multiresolution analysis employing the 2-D wavelet transform [6]. Parametric Bayesian processing presupposes proper modeling for the prior probability density function (PDF) of the resulting signal and noise wavelet coefficients.…”

Section: Statistical Characterization Of Wavelet Subband Coefficientsmentioning

confidence: 99%

“…To justify its use for this particular application we modelled a series of SAR images from the MSTAR Public Clutter dataset 1 . The data set contains X-band images with 1784 x 1476 pixels and 1 ft x 1 ft resolution at ½ Ó depression angles.…”

Section: Alpha-stable Statistical Modelmentioning

confidence: 99%

“…In particular, speckle filtering is an important pre-processing step to improve the overall performance of automatic target detection and recognition algorithms based on SAR images. Recently, there has been considerably interest in using the wavelet transform as a powerful tool for recovering SAR images from noisy data [1,2]. Basically, all waveletbased methods involve as a first step the use of a logarithmic transform to separate the noise from the original image.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

SAR image denoising: a multiscale robust statistical approach

Achim

Bezerianos

Tsakalides

2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628)

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Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. It appears sensible to reduce speckle in SAR images, provided that the structural features and textural information are not lost. We present a novel speckle removal algorithm within the framework of wavelet analysis. First, we show that the subband decompositions of logarithmically transformed SAR images are best described by alpha-stable distributions, a family of heavy-tailed densities. Consequently, we design a maximum a posteriori (MAP) estimator that exploits this a priori information. We use the alpha-stable model to develop a blind speckle-suppression processor that performs a non-linear operation on the data, and we relate this non-linearity to the degree of non-Gaussianity of the data. Finally, we compare our proposed method to current state-of-the-art soft thresholding technique applied on an aerial image and we quantify the achieved performance improvement.

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Wavelet based speckle reduction with application to SAR based ATD/R

Cited by 166 publications

References 9 publications

Speckle Reduction of Synthetic Aperture Radar Images using Median Filter and Savitzky-Golay Filter

Speckle Reduction of Synthetic Aperture Radar Images using Median Filter and Savitzky-Golay Filter

Separated Component-Based Restoration of Speckled SAR Images

SAR image denoising: a multiscale robust statistical approach

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