Abstract
In this paper we discuss the speckle reduction in images with the recently proposed Wavelet Embedded Anisotropic Diffusion (WEAD) and Wavelet Embedded Complex Diffusion (WECD). Both these methods are improvements over anisotropic and complex diffusion by adding wavelet based bayes shrink in its second stage. Both WEAD and WECD produces excellent results when compared with the existing speckle reduction filters. The comparative analysis with other methods were mainly done on the basis of Structural Similarity Index Matrix (SSIM) and Peak Signal to Noise Ratio (PSNR). The visual appearance of the image is also considered.
Keywords
- Synthetic Aperture Radar
- Synthetic Aperture Radar Image
- Anisotropic Diffusion
- Speckle Noise
- Linear Diffusion
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Rajan, J., Kaimal, M.R. (2006). Speckle Reduction in Images with WEAD and WECD. In: Kalra, P.K., Peleg, S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949619_17
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DOI: https://doi.org/10.1007/11949619_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68301-8
Online ISBN: 978-3-540-68302-5
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