The performance of segmentation methods based on watershed depends largely on the gradient of the image.
流域分割方法的性能主要依赖于图像梯度。
Gradient based edge detection methods are mainly focus on step edges.
基于梯度的边缘检测算法，主要是针对阶跃形边缘的检测。
The use of GP model for detecting features has significant advantages over gradient-based feature detection methods which are sensitive to variations in image contrast.
通过理论分析和大量实验，验证了新模型可以可靠地进行低层特征检测，能够服务于不同的视觉信息处理应用。
The use of GP model for detecting features has significant advantages over gradient-based feature detection methods which are sensitive to variations in image contrast.
通过理论分析和大量实验，验证了新模型可以可靠地进行低层特征检测，能够服务于不同的视觉信息处理应用。
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