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cxx6
- 准是指同一区域内以不同成像手段所获得的不同图像图形的地理坐标的匹配。包括几何纠正、投影变换与统一比例尺三方面的处理。在多时相、多信息的复合综合分析时常需... -Standard is the same region acquired by different imaging methods of different geographic coordinates of the image graph matching. Including geometric correction, proj
ppt-triangel
- 本專題分為3大部份 1. 對單一圖片做邊緣檢測後, 統計其複雜度, 再以 Delaunay 三角網來分割複雜度較高的圖形, 將此圖形之三角網的三點座標與RGP值 取樣後壓縮儲存, 及達成壓縮目的. 還原部份為, 以線性內插則是將取樣後的三角網三點內插後還原之原理, 還原單一影像, 再將所有還原之影像串連撥放即完成之影片還原. 2.讀取RS-232接至RFID門禁系統, 讀取Myfair悠遊卡之卡號, 進行身份辨識後, 可選擇需要觀賞之影片.
gbvs_nips
- 显著性分析论文（英文），三个加州理工教授所写。附带有源码是实验Sample（见英文说明中的下载链接）-Saliency Map Algorithm : MATLAB Source Code Below is MATLAB code which computes a salience/saliency map for an image or image sequence/video (either Graph-Based Visual Saliency (GBVS) or the stand
AltitudeGr1867143232005
- Altitude Graph / Line Graph Control. Control is fully functional, but there are several enhancements that would make it better: same old story, couldn t find altitude/graph control so I hacked one together<br><br> i am working on
kmeans_report
- 数据挖掘kmeans图像聚类实验报告 用 VC 或 Java 实现 k-means 聚类算法， 分别以迭代次数及分配不再发生变化为算法终止条件，用图片（自己选择）作为数据集，比较运行时间（画出时间与像素点的关系曲线图，因此须用多幅像素个数不同的图片进行实验） 提交实验报告与源代码。 -Data mining to achieve the k-means clustering algorithm the kmeans image clustering experiment report wit
seg-ijcv
- This paper addresses the problem of segmenting an image into regions. We de¯ ne a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an e±cient segmentation
matlab
- 放大曲线图中的一部分以使图像细节更明显，便于比较不同的曲线结果。同时这也可以使得自己的曲线图看起来更美观。-An enlarged portion of the graph to make the image more clear detail, to facilitate comparison the results of the different curves. Meanwhile it also can make your own graphs look more beautiful.
dynamic-region-merging
- In the proposed algorithm, these two issues are solved by a novel predicate, which is defined by the sequential probability ratio test (SPRT) and the minimal cost criterion. Starting from an over-segmented image, neighboring regions are progressivel
modDRF.pdf
- In this paper we present Discriminative Random Fields (DRF), a discrim- inative framework for the classification of natural image regions by incor- porating neighborhood spatial dependencies in the labels as well as the observed data. The proposed mo
seg-ijcv[1]
- Graph-Based Segmentation 是经典的图像分割算法，该算法是基于图的 贪心聚类 算法，实现简单，速度比较快，精度也还行。-Graph based Segmentation is a classical image Segmentation algorithms, the algorithm is Based on the figure of greedy clustering algorithm, speed is faster, and easy to implement
Hyperspectral-Image-Classification-Through-Bilaye
- Hyperspectral image classification with limited number of labeled pixels is a challenging task. In this paper, we propose a bilayer graph-based learning framework to address this problem. For graph-based classification, how to establish the n