bishe

说明：  数字图像处理 小波处理 ，去噪音，比基于傅里叶变换的去噪方法好。 含噪信号经过预处理，然后利用小波变换把信号分解到各尺度中，在每一尺度下把属于噪声的小波系数去掉，保留并增强属于信号的小波系数，最后再经过小波逆变换恢复检测信号。(The noisy signal is pre-processed, then the signal is decomposed into different scales by wavelet transform. The wavelet coefficients belonging to noise are removed at each scale, and the wavelet coefficients belonging to the signal are retained and enhanced. Finally, the detected signal is restored by inverse wavelet transform. It is better than the denoising method based on Fourier transform.)

自己编写的一个用于人脸识别2dpca程序，很好用的，里面有中文注释(I have written one for the face recognition 2dpca procedures, well used, which has Chinese Notes)

说明：  用于rtd2660方案OSD内字体生成，可以做开机LOGO，无信号界面等(It is used for font generation in OSD of rtd2660 scheme, and can be used for power on logo, signal free interface, etc)

说明：  这是用c语言实现的图形的几何变换算法，里面有许多小的功能(This is achieved using c language graphics geometric transformation algorithms, there are many small function)

Gabor小波进行特征提取，实现人脸识别(Gabor Wavelet Feature Extraction to Achieve Face Recognition)

低时延检测技术分析，包括免调度和信息重传，低时延(Low latency detection technology analysis, including free scheduling and information retransmission)

画图程序 画直线 矩形 圆 椭圆 可填充(draw line .rectangle .circle .roundrectangle. can be filled)

说明：  Legendary server controller for game enthusiasts to study, can

说明：  连通监控视频的 火灾检测，颜色特征，纹理特征等(fire detection Description for each code - extract_red.m, objectlabel.m : Ground Truth labeling automation code generated from Apps - FireDetection.m : MATLAB class to import custom algorithm to Image Labeler - yolov2_detect.m : Entry function for GPU Code generation - GroundTruthTest.mlx : Test code for ground truth labeling - yoloFire_Train.mlx : Training code for YOLOv2 network - Live_Webcam_YOLOv2.mlx : Live webcam demonstration code for YOLOv2 network)

scikit-image: Image processing in Python：Python编写的图像处理程序，可直接调用，是学习python图像处理的很好参考。(scikit-image: Image processing in Python：Image processing program written in Python, can be called directly, is to learn Python a good reference to the image processing.)