Remote Sensing Image Fusion Algorithm Based on Curvelet Transform and Grayscale Measurement Factor
In order to obtain remote sensing images with good spectral features and prominent details,this paper designs a grayscale measurement factor based on the Curvelet transform for remote sensing im-age fusion.Firstly,the brightness component V is extracted from the multispectral image through HSV(Hue,Saturation,Value)transformation.Secondly,the image coefficient is obtained by using the Cur-velet transform.Thirdly,based on the area variance and mean features of image,a low-frequency coeffi-cient fusion operator is established,and by using the grayscale features of high-frequency coefficients to construct a grayscale measurement factor,the richness of image details is measured,and a high-frequen-cy coefficient fusion operator is formed.Finally,under the influence of the Curvelet inverse transform,the updated component(V)of the brightness component V is obtained.The experimental results show that the low-frequency coefficient fusion factor provided in this paper can obtain fused low-frequency coeffi-cients with good spectral characteristics.The grayscale calculation factor studied has a good effect on ob-taining fusion high-frequency coefficients with rich details.
NETL
NSTL
万方数据
