提出一种基于形态学梯度重建的改进快速分水岭分割算法。
A method of watershed segmentation based on morphological gradient reconstructing was proposed.
研究了多种目标提取的数学形态学算法，包括击中与击不中变换、边缘检测与形态学梯度等。
Various algorithms of mathematical morphology are researched, they include hit or miss Transformation, edge detection and morphological grads, etc.
针对这一问题，提出了一种基于形态学梯度的信号噪声分离算法，通过检测信号的边缘实现信号噪声分离。
To solve this problem, this paper proposed a signal noise separation algorithm based on morphological gradient to separate signals from background noise by detecting edges of signals.
在灰值形态学梯度算法和多方位形态结构元素形态学理论分析基础上，提出了提取遥感图像边缘信息的新方法。
Based on morphology grads algorithms and multi-direction morphology structure element of mathematical morphology theory, this paper presents a new method for remote sensing image edge detection.
在改进的边缘检测算法中，本文运用梯度算法对图像进行边缘增强，然后应用最佳阈值算法与形态学方法，取得较好的分割效果。
We use gradient algorithm to enhance cell borders in improving the edge detection algorithm. We achieve a better result through application adaptation threshold algorithm and mathematical morphology.
分水岭变换是数学形态学的主要分割工具，它通过对梯度图像进行分割，能够提供单像素宽的封闭的区域边缘。
Watershed transform is the main tool of mathematical morphology used for image segmentation which can produce one-pixel wide and close edge.
分水岭变换是数学形态学的主要分割工具，它通过对梯度图像进行分割，能够提供单像素宽的封闭的区域边缘。
Watershed transform is the main tool of mathematical morphology used for image segmentation which can produce one-pixel wide and close edge.
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