Hyperspectral Image Denoising by Fusing the Selected Related Bands

Xiangtao Zheng, Yuan Yuan, Xiaoqiang Lu

科研成果: 期刊稿件文章同行评审

43 引用 (Scopus)

摘要

Hyperspectral images (HSIs) convey more useful information than RGB or gray images, which are widely used in many remote sensing tasks. In real scenarios, HSIs are inevitably corrupted by noise because of sensors' imperfectness or atmospheric influence. Recently, many HSI denoising methods have been proposed to utilize the interband information between different spectral bands. However, these methods regard the HSI as a whole and treat the different spectral bands with the same noise level. In fact, the noise levels in different bands are different. Especially, only few certain bands are corrupted by noise, named the target noised bands. Under this circumstance, an HSI denoising method is proposed by considering the band relationship and different noise levels. The target noised bands are adaptively denoised by fusing some selected bands. Specifically, some related but quality superior bands are selected according to the target noised bands. Then, the target noised bands can be denoised by fusing the selected related bands. Experimental results show that the proposed method achieves considerable performances in comparison with several state-of-the-art hyperspectral denoising methods.

源语言英语
文章编号8527652
页(从-至)2596-2609
页数14
期刊IEEE Transactions on Geoscience and Remote Sensing
57
5
DOI
出版状态已出版 - 5月 2019
已对外发布

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