Lu Yanling, Zhou Guoqing, Huang Meiqi, Huang Yaqi
Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China.
College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China.
Sensors (Basel). 2024 Jan 3;24(1):294. doi: 10.3390/s24010294.
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.
传统夜光图像为黑白且分辨率较低,这在很大程度上限制了它们在高精度城市电力消耗估算等领域的应用。因此,本研究提出一种基于双变换(小波变换和IHS(强度、色调、饱和度)颜色空间变换)的融合算法,以生成彩色夜光遥感图像(color-NLRSIs)。在双变换中,将Landsat多光谱图像的红、绿波段与“类NPP-VIIRS”夜光遥感图像进行合并。通过IHS调制小波变换算法将多波段图像的三个波段转换为独立分量,这些分量代表了原始图像的主要有效信息。随着原始图像到IHS颜色空间的变换,得到Landsat多光谱图像的I、H和S分量,并对直方图进行最优匹配,然后将其与二维离散小波变换相结合。最后,将其反演为RGB(红、绿、蓝)彩色图像。实验结果表明:(1)与传统单融合算法相比,双变换在融合前后的空间分辨率、细节对比度和颜色信息方面具有最佳的综合性能效果,因此融合图像质量最佳;(2)融合后的color-NLRSIs能够可视化夜间灯光覆盖区域的特征信息,图像分辨率从500米提高到40米,能够更准确地分析小规模区域的灯光及所覆盖的地面特征;(3)融合后的color-NLRSIs在MEAN(均值)、STD(标准差)、EN(熵)和AG(平均梯度)方面有所改善,使得图像在细节纹理、光谱特征和清晰度方面具有更好的优势。综上所述,双变换算法具有最佳的整体性能和最高质量的融合color-NLRSIs。