提出了一种用于高光谱影像边缘增强的光谱响应曲线差分步长分形维特征值计算方法. 该方法首先对高光谱响应曲线进行差分处理，并利用步长分形维算法计算差分光谱曲线分形维值，最后根据差分分形维值计算高光谱特征影像. 实验结果表明，本文提出的差分步长分形维算法较原始步长法更能保持光谱影像细节并增强边缘，同时减弱噪声影响，可用于高光谱影像特征提取、分析和解译.
In this paper, an algorithm for differential step measurement fractal dimension calculation of the spectrum response curve is proposed for image edge enhancement. A differential spectrum curve is first calculated. A step measurement fractal dimension algorithm is then presented for the differential spectrum curve. Finally, the differential fractal feature image is generated for the feature analysis of hyperspectral images. Experiment results show that the presented algorithm can enhance edges while preserving detailed textures and reducing noise. The proposed method can be used in the feature extraction and analysis of hyperspectral images.
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