Data_Augmentation

用霍夫曼编码，零树小波算法解码，图像处理过程(huffman encode ，ezw decode)

基于加权最小二乘最优化框架的滤波器。可用于实现图像的分层编辑。(Weighted least square)

信息融合滤波算法，基于IMM完成匀速—加速—匀速单运动目标跟踪。(Information fusion filter algorithm based on IMM to complete the uniform and accelerate uniform single moving target tracking.)

说明：  边缘特征的提取就是求图像梯度的局部最大值和方向。实际计算中，以微分算子的形式表示，并采用快速卷积函数来实现。常用的算子有微分算子，拉普拉斯算子，Canny算子等。其中Canny边缘检测是一种较新的边缘检测算子，具有较好的边缘检测性能，得到越来越广泛的应用。Canny边缘检测法利用高斯函数的一阶微分，它能在噪声抑制和边缘检测之间取得较好的平衡(Edge feature extraction is to seek the local maximum of image gradient and orientation. The actual calculation to the form of differential operator representation, and using fast convolution function to achieve. Commonly used operators are differential operators, Laplace operator, Canny operator and so on. Canny edge detection which is a relatively new edge detection operator, and has good edge detection performance, get more and more widely used. Canny edge detection method using first derivative of Gaussian function, it can in the noise suppression and edge detection to achieve a better balance between)

图像显著性，利用Itti视觉显著性分析算法，提取视觉对输入图像的感兴趣部分(Image salient regions)

毕业论文，运用小波分析对图像进行处理，内附源代码(Thesis, the use of wavelet analysis of the image processing included source code)

产生高维的高斯白噪声数据，这在SAR中使用的很多，并且占有重要的地位，主要表现在，SAR去噪这一部分，能更好的成像(White Gaussian noise high-dimensional data, used in SAR lot, and occupy an important position, mainly, SAR denoising this part, better imaging)

说明：  利用R语言编程实现高光谱遥感的随机森林分类(Random Forest Classification Based on Hyperspectral Remote Sensing Using R Language Programming)

基于引导滤波的图像信息分层算法，可实现高低频信息分离，分段处理功能(The image information hierarchical algorithm based on guided filtering can realize the separation of high and low frequency information and the segmentation processing function.)

说明：  应用条件随机场进行图像分割 使用方法：将pydensecrf-py27或pydensecrf-py35重命名为pydensecrf，放入C:Program FilesAnaconda3Libsite-packages 运行：python inference.py im1.png anno1.png out.png(Renameing the file "pydensecrf-py27" or "pydensecrf-py35" to the new name "pydensecrf" Puting this file "pydensecrf" in this directory "C:Program FilesAnaconda3Libsite-packages" cd examples/ python inference.py im1.png anno1.png out.png)