Color Night Light Remote Sensing Images Generation Using Dual-Transformation.
IHS color space transform
color night light remote sensing images
image fusion
multi-source remote sensing
wavelet transform
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
03 Jan 2024
03 Jan 2024
Historique:
received:
09
11
2023
revised:
22
12
2023
accepted:
30
12
2023
medline:
11
1
2024
pubmed:
11
1
2024
entrez:
11
1
2024
Statut:
epublish
Résumé
Traditional night light images are black and white with a low resolution, which has largely limited their applications in areas such as high-accuracy urban electricity consumption estimation. For this reason, this study proposes a fusion algorithm based on a dual-transformation (wavelet transform and IHS (Intensity Hue Saturation) color space transform), is proposed to generate color night light remote sensing images (color-NLRSIs). In the dual-transformation, the red and green bands of Landsat multi-spectral images and "NPP-VIIRS-like" night light remote sensing images are merged. The three bands of the multi-band image are converted into independent components by the IHS modulated wavelet transformed algorithm, which represents the main effective information of the original image. With the color space transformation of the original image to the IHS color space, the components I, H, and S of Landsat multi-spectral images are obtained, and the histogram is optimally matched, and then it is combined with a two-dimensional discrete wavelet transform. Finally, it is inverted into RGB (red, green, and blue) color images. The experimental results demonstrate the following: (1) Compared with the traditional single-fusion algorithm, the dual-transformation has the best comprehensive performance effect on the spatial resolution, detail contrast, and color information before and after fusion, so the fusion image quality is the best; (2) The fused color-NLRSIs can visualize the information of the features covered by lights at night, and the resolution of the image has been improved from 500 m to 40 m, which can more accurately analyze the light of small-scale area and the ground features covered; (3) The fused color-NLRSIs are improved in terms of their MEAN (mean value), STD (standard deviation), EN (entropy), and AG (average gradient) so that the images have better advantages in terms of detail texture, spectral characteristics, and clarity of the images. In summary, the dual-transformation algorithm has the best overall performance and the highest quality of fused color-NLRSIs.
Identifiants
pubmed: 38203156
pii: s24010294
doi: 10.3390/s24010294
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : National Natural Science of China
ID : 41961065
Organisme : Guangxi Science and Technology Base and Talent Project
ID : Guike AD19254002
Organisme : Guangxi Innovative Development Grand Program
ID : GuikeAA18118038 and GuikeAA18242048
Organisme : Guangxi Natural Science Foundation for Innovation Research Team
ID : 2019GXNSFGA245001
Organisme : National Key Research and Development Program of China
ID : 2016YFB0502501
Organisme : BaGuiScholars program of Guangxi
ID : Guoqing Zhou