摘要
针对当前遥感图像融合由于忽略图像边缘信息而出现光谱失真和模糊等问题,提出一种基于梯度锐化的离散小波变换(DWT)算法。首先,利用IHS变换从多光谱图像中提取亮度分量;接着,对亮度分量与全色图像进行离散小波变换来获取图像的高频和低频子带。对于低频子带,依据边缘特征使用梯度锐化准则,完成低频系数的融合;对于高频子带,使用像素区域均值方差最大化的方法,完成高频系数的融合。通过DWT与IHS逆变换得到结果。通过实验发现,设计的方法与当前的光谱锐化方法相比,融合的遥感图像光谱特征及视觉效果更为显著。
Aiming at the problems of spectral distortion and blurring because of ignoring the image edge information,a Discrete Wavelet Transform(DWT) algorithm based on gradient sharpening is proposed.The IHS transform is used to extract the luminance component from the multi-spectral image,and then DWT is executed on the luminance component and the panchromatic image to acquire the high-frequency and low-frequency subbands.For the low-frequency subband,the gradient sharpening criterion is used according to the edge feature to implement the fusion of low-frequency coefficients.For the high-frequency subband,the way of maximizing the MSE of the pixel region is used to complete the fusion of the high-frequency coefficients.The results are obtained by inverse transformation of DWT and IHS.It is found through experiments that the spectral features and visual effects of the fused remote sensing image are better than that of the current spectral sharpening method.
作者
姜文斌
孙学宏
刘丽萍
JIANG Wenbin;SUN Xuehong;LIU Liping(Ningxia University,School of Physics and Electronic-Electrical Engineering,Yinchuan 750021,China;Ningxia University,School o￡Information Engineering,Yinchuan 750021,China;Ningxia Key Laboratory of Desert Information Intelligent Perception,Yinchuan 750021,China)
出处
《电光与控制》
CSCD
北大核心
2020年第5期47-51,共5页
Electronics Optics & Control
基金
宁夏高等学校科学技术研究项目(NGY2017052)。
关键词
遥感图像融合
IHS变换
DWT
梯度锐化
remote sensing image fusion
IHS transform
DWT
gradient sharpening
