摘要
曲波(Curvelet)变换是一种更适合于图像处理的多尺度几何分析(MGA)方法,具有很强的方向性。结合HSI变换将其应用于全色图像和多光谱(MS)图像融合可以更好地表示图像中的有用特征。首先对多光谱图像进行HSI变换,得到亮度分量I,对全色图像和I分量进行曲波变换得到粗尺度系数和细节尺度系数,对全色图像的粗尺度系数和细节尺度系数进行叠加,计算归一化的全色曲波系数直方图,定义边缘有效因子,利用全色图像的特征信息对融合图像的粗尺度系数进行处理,对细节尺度系数采用函数对弱边缘进行增强,对新的曲波系数设计融合规则进行融合,逆变换后得到新的亮度分量Inew,用Inew替代原亮度分量I进行逆HSI变换得到最终融合结果,采用统计类指标对融合结果进行评价。实验结果表明,该方法在保持光谱信息和提高空间分辨率上都有较好的效果。
Curvelet transform, as a method of Multiscale Geometric Analysis （MGA）, is more suitable for image processing than wavelet and more appropriate for analyzing the image edge characteristics of curve and line, and it has better approximation precision and sparsity description. In addition, the representation contains more directional information, and contains more directional information. The methods of integrating PAN image and MS image are proposed based on curvelet transform. PAN image and I image, which is given by a linear HSI transform are given by curvelet transform to obtain coarse coefficients and detail coefficients. The new coarse coefficients are obtained by using edge information and features of PAN image. The detail coefficients are dealt with a function for enhancing faint edges Then, the inverse curvelet transform get the new intensity I image （/new）. Finally, Degree of Distortion （DoD） and Space Frequency （SF） .etc are used to evaluate the result. The results of experiment indicate that the method excels those of based on HSI or curvelet transform in preserving spectral information and enhancing resolution.
出处
《光电工程》
CAS
CSCD
北大核心
2012年第9期18-23,共6页
Opto-Electronic Engineering
基金
国家自然科学基金资助项目(60802084)
西北工业大学基础研究基金项目(JC20110266)
