TY - JOUR
T1 - Hyperspectral Image Denoising by Fusing the Selected Related Bands
AU - Zheng, Xiangtao
AU - Yuan, Yuan
AU - Lu, Xiaoqiang
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - 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.
AB - 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.
KW - Band information
KW - band selection
KW - hyperspectral image (HSI) denoising
KW - image fusion
UR - http://www.scopus.com/inward/record.url?scp=85056322662&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2018.2875304
DO - 10.1109/TGRS.2018.2875304
M3 - 文章
AN - SCOPUS:85056322662
SN - 0196-2892
VL - 57
SP - 2596
EP - 2609
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 5
M1 - 8527652
ER -