duojujiaotuxiangrongheyuandaima

能计算图像的灰度直方图，及其对应的灰度均值(calculate means ，variance，bins)

hslogic算法仿真，基于matlab的灰度共生算法的集成电路裂痕修复仿真(Hslogic algorithm simulation, integrated circuit crack repair simulation based on MATLAB gray level co-occurrence algorithm)

arnold图像置换，可以用于图像加密。(arnold image replacement, can be used for image encryption.)

转换图象为二值图象后，进行识别与标记的matlab源码。可以计算目标物个数，形心等。(image conversion value for the two images, identification and marking of Matlab source. Can be calculated from the number of goals, such as heart-shaped.)

将原图像进行退化处理（选择大气湍流导致图像模糊时相应的PSF），然后将退化后的图像进行复原（使用维纳滤波、直接逆滤波）.(The original image degradation process,and then restore the degraded image with Wiener filtering and inverse filtering.)

：近距离目标超高分辨率微波成像技术在安全检测、非破坏性控制、生物医学等领域中有着非常重要的应用 价值和广阔的应用前景。该文利用基于窄脉冲形式的超宽带时域雷达系统研究近距离目标的高分辨率ISAR成像， 给出了仿真和实测结果。利用转台旋转目标，基于超宽带脉冲源和超宽带收发天线以及高性能取样示波器，配以同 步触发脉冲和自行研发的数据采集软件，搭建了该时域雷达实验系统，提出了准确获取目标回波信息的实验条件， 和实现回波延时精确校正的误差补偿方法。并针对采样时间窗内的杂波干扰，讨论了时域后向投影算法(Back Projection，BP)与背景对消技术相结合的成像算法，实现了分辨率为 8 mm 的近距离目标的成像，准确地反映了 目标的位置、形状和大小等信息。( The high resolution imaging of near field targets are interesting for security, non-destructive control and biomedical application. In this paper, high resolution near field ISAR imaging is implemented using Ultra Wide Band (UWB) time domain radar system. Simulation and experiment are both conducted. The target is rotated by turntable. The system is built based on the UWB pulse source, UWB antennas, high performance sampling oscillograph, synchronous trigger pulse and proper motion study data acquisition software. Experiment condition and delay errors compensation method are presented to obtain accurate echo information of the target. And Back Projection (BP) combined with background cancel algorithm is discussed considering the clutter interference in time window. )

【实例简介】图片转PDF

本算法基于hough变换对图像进行圆检测(hough transform the image circle detection)

说明：  基于hessian矩阵的frangi血管增强算法(An algorithm of vascular enhancement based on Hessian matrix)

Matlab源代码 Incremental Learning for Robust Visual Tracking, International Journal of Computer Vision (IJCV), vol.77, no.1-3, pp.125-141, 2008.(Matlab source code for Incremental Learning for Robust Visual Tracking, International Journal of Computer Vision (IJCV), vol.77, no.1-3, pp.125-141, 2008.)