多光谱图像的边缘特征检测方法
Multispecral Images Edge Detection in Spectral Vector Space
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摘要: 利用多光谱图像的两像素点灰度差异强度指数,定量分析了多光谱图像的边缘特征及响应特征差异,指出传统灰度算子会导致弱边缘特征漏检。为减小边缘响应强度差异,在光谱特征空间中分别利用特征值和特征向量表征多光谱图像的梯度变化大小和方向,同时采用B样条小波对影像进行多尺度变换,获取不同尺度的边缘特征。实验结果表明,此方法对多光谱图像检测出的边缘特征响应均匀且较为显著,综合多尺度边缘能准确检测并定位边缘点,且能有效地抑制噪声。Abstract: Gray level difference index is proposed to quantize the gray level differences between two pixels in a multispectral image theoretically.In the view of Top-of-the-Atmosphere Effect(TOA),the weak information in multispectral image can be suppressed in the strong reflective/rediation field.A novel algorithm is developed to detect edge feature homogeneously and weaken or suppress the effects of TOA.In spectral vector space,the gradient magnitude and direction of a multispectral image is charectrized by the eigenvalues and eigenvectors by the first fundamental form.And dyadic B-spline wavelet transform is applied to obtain edge information in scales from fine to coarse.The results show that the response of gradient is more homogeneous and significant than Canny and Sobel detector results,and integration multiscale edge feature can locate the edge points accurately and ignored the nosie affection.
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