lenaentropy

牛顿环的干涉条纹，灰度图，含有反射图样和透射图样(Newton' s rings interference fringes, grayscale, with reflection and transmission pattern pattern)

) 使用分块的主成分分析方法(PCA)对人脸图像进行压缩编码。针对PCA方法计算量大的缺点,首先把问题转化成奇异值分解(SVD)问题,然后设计了特征空间的更新算法,通过递推,简化每一步计算的计算量,达到了实时编码的要求。 4) 在Windows平台下基于Video for Windows(VFW)接口开发了人脸视频图像编码和解码的实验系统,该系统实现了图像采集、图像显示、编码、解码等功能。() The use of sub-blocks of principal component analysis (PCA) on the human face image coding. PCA method for large defects, first of all the issues into a singular value decomposition (SVD) problem, and then design a feature space of the update algorithm, recursive, simplifying the calculation of the amount calculated at each step to achieve real-time encoding requirements. 4) In the Windows platform based on Video for Windows (VFW) interfaces, the human face image coding and decoding video experimental system, the system achieved image acquisition, image display, encoding, decoding functions.)

详细介绍了matlab下的曲线和曲面拟合，并有一份word的原理说明，介绍的很详细，可供参考和实际运用(Described in detail under the matlab curve and surface fitting, and a word there is the principle that the very detailed introduction is available for reference and practical use of)

说明：  用于图像滤波除噪的频域低通滤波函数，使用MATLAB编程实现(Frequency domain low-pass filtering function for image filtering and de-noising, using MATLAB programming)

经典的图像分割算法ostu,去两峰值之间的峰谷为阀值(Classical image segmentation algorithms ostu, to the peak and valley between two peaks as the threshold)

说明：  用optisystem制作得FBG 滤波器(FBG filter was made with optisystem)

图像检测的算法，Faster R-CNN算法，先对整张图像进行卷积计算，然后通过感兴趣区域池化层(RoI Pooling Layer)将选择性搜索算法推荐出来的候选区域和卷积网络计算出的特征映射图进行融合，得到候选区域对应的特征矢量，这种共享卷积计算的操作极大地减少了卷积计算的次数。而且这些特征矢量的维度统一，方便后续的分类工作。通过感兴趣区域池化层处理卷积特征，并将得到的特征送往两个并行计算任务进行训练，分类和定位回归。通过这些方法和改进的框架，Fast R-CNN 用更短的训练和测试时长，取得了比 R-CNN 更好的效果(Faster R-CNN algorithm first convolutes the whole image, then fuses the candidate regions recommended by the selective search algorithm and the feature mapping maps calculated by the convolution network through the RoI Pooling Layer to get the corresponding feature vectors of the candidate regions, which greatly reduces the number of convolution calculations. Moreover, the dimension of these feature vectors is unified, which facilitates the subsequent classification work. The convolution feature is processed by the pooling layer of the region of interest, and the obtained feature is sent to two parallel computing tasks for training, classification and positioning regression. Through these methods and improved framework, Fast R-CNN uses shorter training and testing time and achieves better results than R-CNN.)

说明：  像素与图像基本指标—彩色图像的基本信息、像素颜色值、图像的大小、矩阵形式等、对灰度图像计算有关统计参数：（1）图像的大小；（2）图像的灰度平均值；（3）图像的自协方差；（4）图像的灰度标准差、对图像进行45度，19度，98度等任意角度的旋转，并计算原图与旋转后图像的相关系数和协方差矩阵(Pixel and Basic Index of Image)

一种可适用于复杂光照环境的低照度图像增强算法，即基于内容感知的自适应对比度提高的增强算法。引入了改进的伽马矫正，可以根据低照度图像的明暗程度自适应的对图像进行预处理。在实验过程中还发现，虽然改进算法有效避免引入大量噪声，但仍有少量噪声存在，为了达到更好的视觉效果，利用改进的双边滤波对增强的图像进行处理，获得最后的增强图像。实验效果显示，该算法可对低照度图像实现理想的增强效果。(A can be applied to complex light environment of low illumination image enhancement algorithm, which based on the content of perception adaptive contrast enhancement algorithm. Introduced the improvement of gamma correction, can according to the low illumination image of light and shade degree adaptive to image preprocessing. In the process of experiment also found that although the improved algorithm effectively avoid introducing a lot of noise, but there still have a small amount of noise, in order to achieve better visual effect, use of improved bilateral filtering to enhance the image processing, finally enhance image. The experimental results showed that the algorithm can achieve a low illumination image enhancement effect. )

说明：  针对相机标准线扩散函数的IDL测试源码，用于相机图像质量评估(IDL test source code for the standard line spread function of the camera, used for camera image quality assessment)