A comparative study on the current de-speckle methods for polarimetric synthetic aperture radar imagery processing

Xu, Zhijia; Sun, Shiyan; Yang, Changcai; Zhang, Xiaobo

doi:10.1117/12.2205580

Cited by 1 publication

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, speckle noise affects the processing accuracy. Recently, various speckle filtering algorithms have been proposed [1][2][3][4] and used in pre-processing to limit the impacts of speckle in these applications. Many such algorithms in the literature [5,6] include Gaussian filtering, spatialpixel feature denoising algorithm, and bilateral filtering used to handle various fundamental noiseremoval tasks [7,8].…”

Section: Introductionmentioning

confidence: 99%

Resolving Interferometric SAR Speckle Problem Using Adaptive GAN

2022

IJIES

View full text Add to dashboard Cite

The interference of reflected waves from multiple elementary scatterers produces speckle, which appears as a granular noise in synthetic aperture radar (SAR) images. These speckles in SAR images cause difficulty in image interpretation, which reduces the effectiveness of image segmentation and classification. In this paper, we propose an effective solution using generative adversarial networks (GAN) to decrease speckle noise while preserving texture features.The convolutional block attention module (CBAM) boosts the essential features in upsampled data and supports the creation of a final denoised real InSAR data.The proposed deep-learning method proved that CBAM enhanced the peak signal-to-noise ratio using the GAN. Furthermore, CBAM improved structural similarity (SSIM) to 99 and achieved the minimum mean squared error. The despeckle performance was enhanced using GAN-ResUNet in which the SSIM equals 0.999. The denoising performance proved that the use of GAN with CBAM as the generator inspired by ResUNeT achieved the best performance compared to other experiments results.

show abstract

Section: Introductionmentioning

confidence: 99%

Resolving Interferometric SAR Speckle Problem Using Adaptive GAN

2022

IJIES

View full text Add to dashboard Cite

show abstract

A comparative study on the current de-speckle methods for polarimetric synthetic aperture radar imagery processing

Cited by 1 publication

References 5 publications

Resolving Interferometric SAR Speckle Problem Using Adaptive GAN

Resolving Interferometric SAR Speckle Problem Using Adaptive GAN

Contact Info

Product

Resources

About