CAJ | 학술논문

提出一种基于邻域方差加权平均的多源遥感图像曲波变换融合方法.将低分辨率的多光谱图像和高分辨率的全色图像作曲波变换,融合图像的曲波系数中的低频分量取多光谱图像的低频分量,中高频系数与高频系数采用邻域方差加权平均的方法由两幅图像曲波变换系数共同决定.逆曲波变换得到融合图像.实验表明算法有效提高了图像的清晰度和保持了光谱特性.
제출일충기우린역방차가권평균적다원요감도상곡파변환융합방법.장저분변솔적다광보도상화고분변솔적전색도상작곡파변환,융합도상적곡파계수중적저빈분량취다광보도상적저빈분량,중고빈계수여고빈계수채용린역방차가권평균적방법유량폭도상곡파변환계수공동결정.역곡파변환득도융합도상.실험표명산법유효제고료도상적청석도화보지료광보특성.
An efficient method of image fusion based on weighted mean and neighboring region variance of curvelet transform is proposed.Firstly,the multi-spectral and high resolution image is decomposed by curvelet transform.Then the curvelet coefficients of the fused image can be obtained by using different rules.The approximate coefficients come from the multispectral image,and the detail coefficient is based on the neighboring region variance.Finally,the fused image is obtained by inverse curvelet transform.The experiment results show that the method can improve the average gradient and preserve spectrum index commendably.