Despeckling of TerraSAR-X Data Using Second-Generation Wavelets

Gleich, Dušan; Kseneman, Matej; Datcu, Mihai

doi:10.1109/lgrs.2009.2020610

Cited by 34 publications

(15 citation statements)

References 14 publications

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“…Haar wavelets with decomposition level of 3 are used as sparse basis for solving (15). The proposed despeckling technique is compared with benchmark and recent despeckling techniques such as Lee [11], Frost [36], Gamma-MAP [13], wavelets shrinkage [14], probabilistic patch based [14], (f) BM3D [18], (g) PPB [19], (h) proposed.…”

Section: Resultsmentioning

confidence: 99%

“…T number of SAR images are reconstructed corresponding to T subsets by using (15). The speckle noise is located in high frequency component of image so sparse reconstruction of image would help eliminate noise in the reconstructed image.…”

Section: Multiple Compressive Image Reconstructionmentioning

confidence: 99%

“…Multiple reconstructed images obtained using (15) are similar in global perspective but statistically different in local perspective as all these images are reconstructed by using different sets of pixels. It is well known that statistical processing of multiple observations of same scene help reduce additive and multiplicative noise.…”

Section: Selective 3-d Filteringmentioning

confidence: 99%

“…The image obtained by employing (19) is despeckled image. In the proposed framework speckle is reduced by imposing dual mechanisms; through inherent noise reduction via compressive reconstruction (15) and selective 3D filtering (19). Therefore, the proposed framework leads to better speckle reduction compared to benchmark despeckling algorithms.…”

Section: Selective 3-d Filteringmentioning

confidence: 99%

“…With the development of multi-resolution analysis theory, wavelet transformation methods are often used for despeckling [14,15]. In Wavelet shrinkage techniques, wavelet transform coefficients are thresholded.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Sar Image Despeckling by Selective 3d Filtering of Multiple Compressive Reconstructed Images

Iqbal¹,

Chen²,

Yang³

et al. 2013

PIER

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Abstract-A despeckling technique based on multiple image reconstruction and selective 3-dimensional filtering is proposed. Multiple SAR images are reconstructed from a single SAR image by employing compressive sensing (CS) theory. In order to obtain multiple images from single SAR image, multiple subsets of pixels are selected from input SAR image by imposing restriction that each subset has at least 20% different pixels from any other subset. These subsets are taken as measurement vectors in CS framework to obtain multiple SAR images. A despeckled image is obtained by employing selective 3-dimensional filtering to multiple reconstructed SAR image. The proposed technique is tested on single look complex TerraSAT-X data set, and experimental results exhibit that the proposed technique outperformed benchmark despekling methods in terms of visual quality and despeckling quality metrics.

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