图象平滑处理系统,主要实现对图像边沿的平滑处理。
Image Processing System, the main achievement of the 2500 image smoothing.
细胞图象增强主要采用灰度变换、直方图修正、图象平滑、图象锐化等方法。
The method of enhancing the cell image include gray-scale transformation, histogram modification, image smoothing and image sharpening etc.
预处理包括图纸扫描输入、图象二值化、图象平滑与去噪、线条细化和曲线跟踪。
The preprocessing steps include drawing scanning, binary image transforming, line thinning and cure tracing.
利用高斯函数得到了图象平滑去除随机噪声中使用的平滑模板的一个较普遍的公式。该公式为图象平滑去除噪声提供了多种模板选择。
A more common formula of templates used in image smooth denoising is developed from Gauss function in order to offer more templates to be chosen when denoising images with random noise.
同时,在不灵敏频带内(如图象边缘区)引入一定噪声以达到整个恢复图象的噪声平滑。
Meanwhile, some noises are added into frequency bands where it is less visible in order to achieve noise smooth of overall reconstructing image.
这种方法不仅能够有效地平滑噪声,还能够锐化模糊的图象边缘;
With this method, not only the noise can be smoothed efficiently, but also the blurred edge of an image be sharpened.
并利用这一原则实现了二值图象的多种cnn平滑算法。
And the principle is also used to achieve some CNN smoothing algorithms for binary images.
针对边界部分有重叠的图象,提出了一种基于网格匹配的快速对准算法,并通过平滑因子对图象实现了无缝拼接。
In this paper, we present a fast stitching algorithm for the overlapping images based on grid matching, which makes images matching correctly, stitching images seamless and smooth.
提出宫颈癌细胞图象的数据采集,原始图象的平滑与边缘增强、分割与边界跟踪等处理方法。
Pressents a method for the data acquisition of cervical cancer cell image, the smooth, boundary enhancement, segmentation and edge track of original image.
为了定量地评价这种平滑方法的性能,本文对计算机产生的试验图象定义了一种图象优值,作为评价的指标。并且通过实验将这种平滑方法的性能与梯度的倒数加权平均法、中值滤波法进行了比较。
In order to evaluate the performance of the proposed method quantitatively, a figure of merit for the test image generated by computer is defined and used as a measure of evaluation.
为了定量地评价这种平滑方法的性能,本文对计算机产生的试验图象定义了一种图象优值,作为评价的指标。并且通过实验将这种平滑方法的性能与梯度的倒数加权平均法、中值滤波法进行了比较。
In order to evaluate the performance of the proposed method quantitatively, a figure of merit for the test image generated by computer is defined and used as a measure of evaluation.
应用推荐