fusion

echarts-master  

时频分布处理（重排、图像的信息处理以及Winger-Hough变换）(Time-Frequency Distribution Processing (rearrangements, the image information processing and the Hough transform Winger))

用MATLAB实现从颜色空间hsi到rgb空间的转换。(MATLAB hsi from color space to the rgb space conversion.)

基于FCM的彩色图象的分割的MATLAB源代码(FCM-based segmentation of color images of the MATLAB source code)

正反馈主动频率偏移法，是应用于孤岛检测的一种算法，可以减小检测盲区，加快孤岛检测速度(Positive feedback active frequency offset method is an algorithm used in islanding detection)

说明：  该算法的功能是实现时频分析中多种分析方法后续处理中的图像压缩功能，进一步提高图像的时频分辨率(The function of the algorithm is to realize the image compression function in the subsequent processing of various analysis methods in time-frequency analysis, and further improve the time-frequency resolution of the image)

直方图均衡化，包括动态直方图均衡化，全局直方图均衡化，局部直方图均衡化，以及绘制图像的直方图 其中动态直方图均衡化用A dynamic histogram equalization for image contrast enhancement 只取x=0情况(Histogram equalization, including dynamic histogram equalization, global histogram equalization, local histogram equalization, and where to draw the image histogram dynamic histogram equalization with A dynamic histogram equalization for image contrast enhancement only take x = 0 Happening)

说明：  图像处理，运动放大，视频代码展示，以及输出结果(steerable pyramid algorithm)

现有自然图像素描画效果生成算法存在容易造成画面细节丢失，笔画线条单一等问题。针对这些问题，本文提出了一种改进的自然图像素描画效果生成算法，通过模拟艺术家创作素描画过程，分步生成素描画图像底纹和素描画场景笔画轮廓，采用8个方向卷积滤波提取图像中不同方向的细节信息，并使用不同长度不同粗细的笔画来模拟艺术家在创作过程中不同力度的绘画效果，最后合并素描画笔画效果和素描画图像底纹，得到与原输入自然图像内容一致，色调与艺术家绘制的素描画效果相同，笔画和底纹形式与实际素描画相似，真实感较强的素描画效果输出图像。大量实验结果表明本文方法可以生成高质量的自然图像素描画效果，与现有成熟的铅笔画生成技术相笔，本文方法具有较强的可比性。(The existing algorithms for natural image sketch production are easy to cause some problems such as the loss of image details, singleness of the stroke line. To solve these problems, this paper proposes an improved algorithm for the natural image sketch effect producing. By simulating the artist creation process of sketch, step-by-step generate image shading sketch image shading and drawing the scene outline stroke of the sketch image, using 8 directions of convolution filter to extract the details of different directions in the image, furthermore, using the stroke of different length and thickness to simulate the painting effect of different strength in the process of artist creation, finally we merge the sketch stroke effect and sketch image background to get the output image, which have consistent content with the original input image, have the same tonal effect with artists draw sketch, have the similar Stroke and background form with the actual sketch and have strong real sense in)

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.)