compressed-sensing

说明：  1.使用medfilt2函数对‘lena.bmp’进行不同模板大小的中值滤波，并观察效果 2.使用fspecial函数构造‘gaussian’, ‘sobel’, ‘prewitt’, ‘laplacian’, ‘average’等不同滤波算子，使用filter2函数对‘cameraman.tif ’进行滤波，观察不同滤波器的效果 3.设计频域理想低通和理想高通滤波器，对‘phantom.bmp’图像进行频域滤波，显示滤波结果。然后改变截止频率，观察对结果的影响。 4.对‘homo.bmp’进行同态滤波，其中频域同态滤波器自行设计。要求在程序注释中说明你设计该滤波器的思想。(1' lena.bmp 'The median filtering with different template sizes was carried out and the effect was observed2. Fsspecial function is used to construct different filter operators such as' Gaussian ',' Sobel ',' Prewitt ',' Laplacian ',' average ', etc' cameraman.tif 'Filter and observe the effect of different filters3. Design ideal low pass and ideal high pass filters in frequency domain' phantom.bmp 'The image is filtered in frequency domain and the filtering result is displayed. Then change the cut-off frequency and observe the effect on the results.4. Yes' homo.bmp 'The homomorphic filter is designed by ourselves. The idea of designing the filter should be explained in the program notes.)

文档介绍了大量离散实验数据的平滑滤波处理方法(Document describes a large number of discrete experimental data smoothing filter processing method)

针对彩色图像的局部直方图均衡化，可以较好的增强图像细节(poshe,it can enhancements the detail of the image )

Level set solver for two phases flow

Image Database 2.5.0 (w/ thumbnails)

c#编写的图像平滑处理，源码比较全，可以成功编译，希望对大家有帮助。(c# prepared by the image smoothing, source code comparison, can be successfully compiled, we want to help.)

训练了一个CNN模型用于土地资源分类，适用于遥感图像(A CNN model is trained for land use classification and is suitable for remote sensing images.)

完成流程编码和huffman编码，适合做图像编码的熵编码，只要调整接口就好。(Complete the process encoding and huffman coding, image coding suitable for entropy coding, as long as the adjustment of the interface is like.)

利用高斯金字塔原理进行连续的图像序列的压缩。需要将图像序列连续命名。输出为压缩图像。(Gaussian pyramid principle compress continuous image sequences. Need the image sequence continuously named. Output is compressed image)

利用最大熵方法求图像二值化的阈值 输入的图像名称，读取名称是M的图像文件 统计各个灰度级出现的概率 (Using the maximum entropy method for image binarization threshold input image name, the name is M read image files in various gray-scale statistical probability)