Open AccessSAR image denoising method based on sparse representation
Author(s) -
Zhou HaoTian,
Chen Liang,
Fu Bo,
Shi Hao
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0328
Subject(s) - speckle noise , multiplicative noise , artificial intelligence , synthetic aperture radar , computer science , transformation (genetics) , computer vision , noise (video) , noise reduction , image (mathematics) , pattern recognition (psychology) , speckle pattern , logarithm , image restoration , image processing , mathematics , mathematical analysis , biochemistry , chemistry , signal transfer function , digital signal processing , analog signal , gene , computer hardware
The coherent nature of radar illumination causes the speckle effect, which gives the synthetic aperture radar (SAR) image its noisy appearance. The probability distribution of speckle noise is multiplicative rather than additive, which makes the interpretation and processing of SAR imagery more difficult. A novel SAR image denoising method is proposed. First the multiplicative noise is transformed into additive‐like noise by logarithmic transformation. After that, a novel object function is proposed which combines a pre‐trained dictionary model to deal with the image. Finally, exponential transform is employed to recover the image. Experimental results show that the proposed method can effectively remove the noise of SAR images, and indicate good performance compared with other state‐of‐the‐art methods.