Proceedings ArticleDOI
Quantitative approach of speckle noise reduction on synthetic Aperture radar images
R. Vijaya Geetha,S. Kalaivani +1 more
- pp 1-4
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TLDR
The main objective of this paper is to present a quantitative approach of de-specking algorithm on SAR images with adequate mathematical parametric analysis.Abstract:
Over the past three to four decades the SAR-synthetic Aperture Radar imagery has become a beneficial and important application over the optical Satellite imagery, Because of its ability to operate in all-weather condition and capability of all time data acquisition; The main issue in this imaging technique is presence of grainy noise termed as ‘speckle’, Which will affect the overall quality of image, hence it is highly required to use effective speckle reduction techniques to suppress speckle. Various filtering techniques are available to reduce the speckle noise and to enhance the quality of the image. The main objective of this paper is to present a quantitative approach of de-specking algorithm on SAR images with adequate mathematical parametric analysis.read more
Citations
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Journal ArticleDOI
De-Speckling of SAR Images with Fuzzy Filters along with Altered Preserved Edge Values
TL;DR: In this paper , a new technique has been proposed which preserved the edge pixels by fuzzy edge detection method and then altered with the filtered image-pixels by fuzzy filtration for getting the de-noised image.
Book ChapterDOI
Automated Speckle Noise Suppression from Sentinel-1A Synthetic Aperture Radar Imagery Using Adaptive Filtering Techniques
TL;DR: In this paper , despeckling is performed by applying MAP, Lee, Frost, Kuan and Boxcar adaptive filtering techniques with 3 × 3, 5 × 5 and 7 × 7 sized kernels.
References
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Journal ArticleDOI
Speckle analysis and smoothing of synthetic aperture radar images
TL;DR: This paper develops a statistical technique to define a noise model, and then successfully applies a local statistics noise filtering algorithm to a set of actual SEASAT SAR images, resulting in smoothed images that permit observers to resolve fine detail with an enhanced edge effect.
Journal ArticleDOI
Analysis, Evaluation, and Comparison of Polarimetric SAR Speckle Filtering Techniques
TL;DR: Results show that filters performances need to be assessed using a complete set of indicators, including distributed scatterer parameters, radiometric parameters, and spatial information preservation.
Journal ArticleDOI
An Adaptive Method of Speckle Reduction and Feature Enhancement for SAR Images Based on Curvelet Transform and Particle Swarm Optimization
TL;DR: An adaptive method based on the mirror-extended curvelet transform and the improved particle swarm optimization (PSO) algorithm, which reduce speckle noise and enhance edge features and contrast of synthetic aperture radar (SAR) images and outperforms the wavelet- and curvelet-based nonadaptive despeckling and enhancement methods.
Journal ArticleDOI
A Recursive Filter for Despeckling SAR Images
TL;DR: This correspondence proposes a recursive algorithm for noise reduction in synthetic aperture radar imagery by incorporating a discontinuity-adaptive Markov random field prior within the unscented Kalman filter framework through importance sampling.
Journal ArticleDOI
Speckle suppression using recursive wavelet transforms
TL;DR: The quantitative analysis is carried out and compared with the results of some existing filtering algorithms including median, K nearest neighbour averaging, Lee's multiplicative and Crimmins' geometric filters, showing that imagery filtered by the wavelet transform is the smoothest.