Abstract
In this work speckle reduction methods defined in the literature are basically compared according to effect on classification, edge preservation and noise reduction in homogenous regions. The methods are tested on labeled SAR image, simulated SAR image and optical image. It is aimed to present mutual effect of speckle reduction methods on both edge preservation and noise reduction. One of the purposes of this work is to improve SRAD method, which is especially defined for speckle noise reduction, by combining it with Canny edge detection and Gauss filtering. It is proved by the experimental results that proposed method enhances the quality measure results.
Keywords
Speckle noise
Speckle pattern
Anisotropic diffusion
Noise reduction
Artificial intelligence
Computer vision
Canny edge detector
Reduction (mathematics)
Computer science
Noise (video)
Gauss
Enhanced Data Rates for GSM Evolution
Edge enhancement
Edge detection
Image (mathematics)
Image enhancement
Mathematics
Image processing
Physics
Subject Areas
Image and Signal Denoising Methods
·Computer Vision and Pattern Recognition ·Physical Sciences
Advanced Image Fusion Techniques
·Media Technology ·Physical Sciences
Advanced Image Processing Techniques
·Computer Vision and Pattern Recognition ·Physical Sciences
Citations by Year
2013: 1
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