资源列表
hessian
- 实现了海森矩阵，改进了微分求导部分，有详细的注释说明，针对医学图像效果明显。-To achieve the Hessian matrix, improved differential derivation section, there are detailed notes, for obvious medical image effect.
xiangjian_hessian
- 先进行图片相减，再进行海森变换，可提取图片中的变化区域。-First image subtraction performed, then Hassan transformation can extract picture change area.
xiangjian_yuzhi
- 针对相似图像，提取其不同的部分。采用先相减再进行阈值判断。-For similar images extracted different parts. Then subtract using the first threshold value judgment.
TImageColorspace
- 各种颜色空间的转化 史上最全的 有RGB HSI HSV Ycbcr LAB -The history of the various color space conversion has the most complete RGB HSI HSV Ycbcr LAB
gaijin_hessian
- 一种改进后的海森矩阵算法代码，针对医学图像处理效果比较好，可以识别较细的血管。-An improved Hessian matrix algorithm code, medical image processing effects for better, you can identify smaller vessels.
Gabor
- 定义了三个Gabor滤波器函数，并在主函数中一一调用，都可正常运行，对医学影像的处理效果较好。参数可自行调节。-It defines three Gabor filter function, and 11 calls in the main function, can be normal operation, the medical image processing better. The parameter can adjust itself.
mstar_conv_tools
- 这些程序可以将MSTAR数据库中的数据转换为可是图像，例如JPEG和TIFF，方便SAR图像的处理。-These program can convert the MSTAR data into some images such as jpeg and tiff.It s easy to study sar images.
test_gray_gradient
- 将一幅图像划分成8*8图像块，计算灰度梯度共生矩阵，基于混合熵对每个图像块分类-divide an image into 8*8 image blocks,calculate gray-gradient-matrix, classify image blocks based on the mixed entropy
ShowRGB
- OpenCv实现鼠标移动显示图像RGB值-show RGB value of the point in the picture using Opencv
sblb
- 经典的双边滤波程序，可以用于图像去雾处理，具有较好的实用性。-Classic bilateral filtering process, can be used for image processing, has good practicability.
Chan-Vese-model
- Chan-Vese模型是基于区域的几何活动轮廓模型,此模型根据灰度级的同质性进行分类，图像域包括背景区域与前景区域。-Chan-Vese geometric model is region-based active contour model, this model are classified according to the gray level of homogeneity, including the background image field area and the foregro
Natural-Image-Matting
- 影像抠图的目的是利用有限的样本，从影像背景中提取前景目标，并估计前景的透明度，即前景掩膜-The purpose is to use image matting limited sample, extract foreground objects the background image, and estimate the prospects of transparency, that the prospects mask