ieee_ssr_bench

说明：  这篇论文提出了一种较好的水下图像增强的方法。首先使用经过端到端训练的卷积神经网络去测量输入图片，同时以自适应双边滤波器对传输图片进行处理。接着提出一种基于白平衡的策略来消除图片的颜色偏差，用拉普拉斯金字塔融合获得无雾和色彩校正图像的融合结果。 最后，输出图像被转换为混合小波和方向滤波器组（HWD）域，用于去噪和边缘增强。 实验结果表明，该方法可以消除颜色失真，提高水下图像的清晰度。(This paper proposes a better underwater image enhancement method. Firstly, an end-to-end training convolutional neural network is used to measure the input image, and an adaptive bilateral filter is used to process the transmitted image. Then a strategy based on white balance is proposed to eliminate the color deviation of images. The fusion results of fog-free and color correction images are obtained by Laplacian pyramid fusion. Finally, the output image is converted into hybrid wavelet and directional filter bank (HWD) domain for denoising and edge enhancement. The experimental results show that the method can eliminate color distortion and improve the clarity of underwater images.)

测试Glew开发环境搭建是否成功，如果您成功的安装了对应的glut和glew库文件。(the test code for glew, to know is it working.)

电压跌落是最严重的动态电能质量问题之一， 精确定位电压跌落起止时间是应对电压跌落问题的 重要前提和基础。由于电压采样信号往往有噪声分 量，现有的方法在定位电压跌落的起止时间时存在 局限性。本文提出利用多小波变换及相邻系数去噪 的电压跌落定位方法。多小波兼有对称性、正交性、 有限支撑性和二阶消失矩等优异的信号处理性能， 利用GHM多小波可以准确定位电压跌落起止时间。 多小波变换系数在每层之间具有对应关系，多小波 相邻系数将紧相邻的若干个系数作为一个整体来确 定阈值，考虑了系数之间的相关性，能获得更好的 去噪效果。通过 Matlab 进行仿真验证，仿真结果表 明，所提出的方法的正确性。 (Voltage sag is one of the most serious dynamic power quality problems. Critical start-time and end-time are important indices for voltage sags. But the sampling signals often have noisy component, the locations of start-time and end-time are hard to get. Wavelet is an effective tool for those non-stationary signal processing and has been used in this field. Local feature in the signal can be enlarged after the transformation using the scalar wavelet. But scalar wavelets cannot contain orthogonality, symmetry, compact support and higher order of vanishing moments simultaneously. In this thesis, multi-wavelets GHM is used to detect and locate power quality disturbances. Multi-wavelets offer many excellent properties such as the same approximation order but more compact support. The dependence of the multi-wavelets coefficients varies with the level, so neighboring coefficien)

均值滤波去噪声程序，效果显著，已经通过调试(Mean filter to the noise process, achieved significant results, have been through the debugging)

< 数字图像处理算法及应用>这本书的相关代码(Image Processing Algorithm and Practices is an important book in IP and AI. High-pass Filter is very normal and practical tool.)

对图像进行压缩，算术编码实现程序和仿真图象，给出基于 DCT 的图像压缩的 matlab 仿真结果(Image compression, arithmetic coding implementation program and simulation image, the image compression based on DCT matlab simulation results)

使用matlab进行图像去雾，有助于帮助刚入门的图像小白学习matlab图像处理(Matlab image defogging, helpful to help beginners learning image white matlab image processing)

说明：  该程序用Delphi7.0实现，中文名称：血液红细胞识别与统计系统，可以识别一幅图片中的血红细胞并统计出个数，准确率达到90％以上，该程序包含了用Object Pascal语言处理图像的一些基本常用技巧，值得一看(Delphi7.0 realize with the program, Chinese name: blood red blood cell identification and statistical systems to identify a picture of the red blood cells and a number of statistical accuracy rate over 90, the program includes the use of Object Pascal language processing images some basic common skills, worth a visit)

说明：  基于空间信息的模糊均值聚类算法，SFCM，适用于数据分析，图像分割(space fuzzy-c-means clustering algorithm)

1.本程序主要处理BMP位图。 2.为了方便读者学习，程序各步骤都被拆分开实现了，通过点击相应按钮可以看到每个步骤处理的结果。 3.如果是进行人脸识别，需要先打开一幅位图依次进行“人脸检测与定位”操作和“人脸特征标注”操作，然后再打开需要比较的第二幅位图，也是依次进行所有操作，最后进行识别以区分先后两个人脸。(This procedure deals mainly with BMP Bitmaps. 2. In order for the reader to learn, each step of the program is split and the results of each step can be seen by clicking the appropriate button. 3. In the case of face recognition, it is necessary to open a bitmap for "face detection and location" and "face feature tagging" in turn, then open the second bitmap to be compared, and then perform all the operations in turn, and finally identify to distinguish two faces in succession.)