cvprcode

fcm 及快速fcm实现图像分割，还带有GUI界面(fcm fcm and fast image segmentation, but also with GUI interface)

几种基本的CFAR检测方法的比较，各种杂波背景分布的参数估计方法等等(Comparison of basic types of CFAR detection method, a variety of clutter distribution parameter estimation methods, etc.)

基于matlab的进行鸡蛋形状特征提取的程序，能提取鸡蛋裂缝区域的形状特征(Matlab based on the conduct of an egg shape feature extraction procedure can extract the shape of an egg cracks in the regional characteristics of)

分别采用RGB模型和HIS模型对图像imageLane.bmp进行锐化，并比较锐化的效果是否相同（两锐化后的图像相减）。(RGB model and HIS respectively model imageLane.bmp sharpening the image and to compare the effect of sharpening is the same ( sharpen the image after the subtraction).)

帅选出人体,yolo人员检测，yolo模型，并识别(peole detect and get the pix point of it ,)

点云数据（圆柱面）

粒子滤波与PHD多目标跟踪比较，三目标分别进行粒子滤波和marginalPHD滤波跟踪比较结果。(PHD particle filter multi-target tracking compared with the three goals were to filter tracking particle filter and marginalPHD comparison.)

Zhang等人 利用相位一致性信息的特性，提出了 特征相似性方法(FSIMG) ，选取了相位一致性信息和梯度信息 作为它的两个特征，得到了较好的结果。 (A novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features. Specifically, the phase congruency (PC), which is a dimensionless measure of the significance of a local structure, is used as the primary feature in FSIM. Considering that PC is contrast invariant while the contrast information does affect HVS’ perception of image quality, the image gradient magnitude (GM) is employed as the secondary feature in FSIM. PC and GM play complementary roles in characterizing the image local quality. After obtaining the local quality map, we use PC again as a weighting function to derive a single quality score. Extensive experiments performed on six benchmark IQA s demonstrate that FSIM can achieve much higher consistency with the subjective uations than state-of-the-art IQA metrics.)

根据MPEG7中图像的SCD描述算子，提取图像在HSV空间中的直方图。并且可以与源图像进行比较。(MPEG 7 Scalable Color Descriptor experiment)

Matlab环境下的几个数字图像处理实验，包含图像灰度变换、直方图均衡化、直方图匹配、邻域平均、局域增强、中值滤波、图像的锐化等(Several digital image processing experiments, including gray transform, histogram equalization, histogram matching, neighborhood average, local increase, median filtering and image sharpening, etc.)