资源列表
ArcGIS-Engine-CSharp
- ArcEngine+C#开发教程，希望对初学者有用-ArcEngine+ C# development tutorial, I hope be useful for beginners
Mulil
- Multispectral remotely sensing imagery with high spatial resolution, such as QuickBird, IKONOS satellite imagery or Aerial imagery, especially in urban scenes, often perform spectral variations and rich details within a category, resulting in
final2
- 基于数字摄影测量中的VLL法（铅垂线轨迹法）实现了基于物方的影像匹配-Based on VLL method in digital photogrammetry(vertical line locus method) to achieve a square image matching based on object space
nehelesson
- Hene opengl教程的所有源代码，基于visual basic 开发环境-Hene opengl tutorial all the source code, visual basic development environment based on
Otsu-threshold-segmentation
- 吴一全等采用灰度级-梯度级构建二维直方图，并提出快速迭代算法。改进的二维Otsu法阈值分割快速迭代算法。-Wu congruent grayscale- gradient level to build a two-dimensional histogram, and a fast iterative algorithm. Improved dimensional Otsu threshold segmentation fast iterative algorithm.
Bspline
- B样条曲线绘制，均匀样条，准均匀样条绘制-B-spline curve drawing, uniform spline quasi-uniform spline drawing
32Picking
- 使用VisualC++ Win32应用程序开发的一个OpenGL程序，在OpenGL中实现拾取的效果。 -Using VisualC++ Win32 OpenGL application development of a procedure implemented in OpenGL pick up results.
TestEdge
- 对图像中不同形状的图像进行分析，提取，并可求出面积，内带测试图片-pick up some form from the picture, and calculate the area. it takes the photo
traffic-electronic-map
- 用VC开发的交通电子地图，包含可运行的程序及所有源码。-VC traffic with the development of electronic map, and contains all the source code to run the program.
yixuetuxiangpeizhun
- 本文借助多尺度分析为手段， 研究医学图像配准与融合过程中医学图像的增强、插值、配准、融合和分割等 关键问题的理论方法研究，扩展了尺度的含义，使其不再局限在通常的小波分 析和形态学两个方面。-In this paper, using multi-scale analysis as a means to study the medical image registration and fusion process of medical image enhancement, interpo
基于小波变换的不同分解层次去噪
- 包含不同分解层次对图像去噪效果的仿真程序及结果，包含信噪比源程序(Contains different decomposition levels of image denoising effect of the simulation procedures and results, including signal to noise ratio source)
hed-master
- We develop a new edge detection algorithm, holistically-nested edge detection (HED), which performs image-to-image prediction by means of a deep learning model that leverages fully convolutional neural networks and deeply-supervised nets. HED automat