Description: 图像处理的程序实现，基于matlab，但是没有直接采用matlab的相关语句。 内容包括：1.图像灰度直方图的显示、灰度直方图的计算
2.图像的几何变换——水平镜像图、垂直镜像图、水平错切图、垂直错切图 3.图像的平滑、锐化滤波 4.图像的阈值分割 运行程序的main函数，根据提示进行操作即可
-image processing program, based on Matlab, But not directly related to the use of Matlab statement. Contents include : 1. The image histogram, Histogram calculation 2. Image geometry transformation-- mirroring the level map, vertical image map, the level of cutting the wrong map vertical Shear Figure 3. the image smoothing, sharpening filter 4. Image segmentation threshold operational procedures for the main function, According to the instructions can operate Platform: |
Size: 3072 |
Author:张焕人 |
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Description: In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to convert a given gray level MR image in to a color space image and then separate the position of tumor objects from other items of an MR image by using c means clustering
And histogram clustering .Experiments demonstrates that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.
-In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to convert a given gray level MR image in to a color space image and then separate the position of tumor objects from other items of an MR image by using c means clustering
And histogram clustering .Experiments demonstrates that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.
Platform: |
Size: 2048 |
Author:pramod |
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Description: 算法步骤：
（1） 计算图像直方图，灰度级为Ns，图像的平均灰度值为Tc；
（2） 分别计算第一个灰度级和其余灰度级的信息熵并求和，前两个灰度级和其余灰度级的信息熵并求和，以此类推计算Ns个和；
（3） 找到H在Tc附近最大值的位置Tenf即为阈值；
（4） 图像中大于阈值的像素置1，其余置0而实现二值分割。
算法的核心：信息熵越大越有不确定性，分割出的图片越好。(Algorithm steps:
(1) the histogram of the image is calculated, the gray level is Ns, and the average gray value of the image is Tc.
(2) calculate the information entropy of the first gray level and the rest of grayscale, and sum up the information entropy of the first two grayscale and the rest gray level, and calculate Ns sum by analogy.
(3) to find the location of the maximum value of H near Tc, Tenf is the threshold;
(4) 1 pixels larger than the threshold in the image, and the rest 0 to achieve the two value segmentation.
The core of the algorithm: information entropy is more uncertainty, the segmented image.) Platform: |
Size: 71680 |
Author:leo小野兽 |
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