IKONOS图像融合中自动拟合低分辨率全色图像的方法

An Automatic Method of Simulating Low Resolution Panchromatic Image in IKONOS Image Fusion

提出了一种IKONOS图像融合中自动拟合低分辨率全色图像的方法。首先使用支持向量机将全色图像的像元自动分为高、低频信息像元;然后采用改进的Bucket技术选择一定数量、均匀分布的低频信息像元点作为观测值;最后通过线性回归方法求得拟合系数,并构造低分辨率全色图像。两组IKONOS全色与多光谱图像的实验结果表明,本文方法能自动选择均匀分布的像元点,并求得拟合系数,基于拟合低分辨率全色图像的Gram-Schmidt融合方法的质量也优于传统的Gram-Schmidt融合方法。

An automatic method of simulating low resolution panchromatic image in IKONOS image fusion was described.Firstly,support vector machine（SVM） was used to separate pixels containing low frequency information from those containing high frequency information,which was not suitable to be included in regression coefficients estimating.Secondly,improved Bucket technique was adopted to generate a subset of observations evenly distributed.Finally,low resolution panchromatic image was simulated with parameters achieved by linear regression,and integrated into the Gram-Schmidt spectral sharpening method.Validating experiments were carried out on two datasets of IKONOS panchromatic and multispectral images,visual and quantitative quality judgments show that the proposed method can select evenly distributed pixel observations with low frequency information automatically,which proves its high efficiency,and that the resultant images have less spectral distortion than traditional Gram-Schmidt method does.