.png){kind=icon}
.png){kind=icon}
Return
SAR Image Despeckling Using Data-Driven Tight Frame
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2013.2291937.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Data-driven sparse representation of images has been shown to be efficient approaches to image denoising. Following this observation, a novel technique is developed in this letter for reducing the speckle in synthetic aperture radar (SAR). This technique is conducted first by converting the multiplicative noisy image into a tractable additive one by taking logarithms. Then, a discrete data-driven tight frame is derived from the logarithmic transformed image and used for noise removal. Numerical experiments suggest that the proposed scheme not only runs relatively fast owing to the adoption of tight frame but also achieves comparable performance in comparison with some state-of-the-art methods.
Keywords:
Sparse approximation
speckle
tight frame
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
16.4
Papers:
1.0W
Citations:
5.1K