基于python的数字图像处理实验源码+详细代码注释+实验说明文档.zip

[{"title":"（ 25 个子文件 788KB ） 基于python的数字图像处理实验源码+详细代码注释+实验说明文档.zip","children":[{"title":"项目说明.md <span style='color:#111;'> 586B </span>","children":null,"spread":false},{"title":"4th","children":[{"title":"Image_segmentation.py <span style='color:#111;'> 1.18KB </span>","children":null,"spread":false}],"spread":true},{"title":"2th","children":[{"title":"Salt&pepper_noise.py <span style='color:#111;'> 1.38KB </span>","children":null,"spread":false},{"title":"Gaussian_noise.py <span style='color:#111;'> 1.33KB </span>","children":null,"spread":false}],"spread":true},{"title":"1th","children":[{"title":"4.Linear_contrast_broadening.py <span style='color:#111;'> 1.22KB </span>","children":null,"spread":false},{"title":"2.RGB_to_GRAY.py <span style='color:#111;'> 646B </span>","children":null,"spread":false},{"title":"5.Gray_window.py <span style='color:#111;'> 1.21KB </span>","children":null,"spread":false},{"title":"3.Histogram_equalization.py <span style='color:#111;'> 403B </span>","children":null,"spread":false},{"title":"1.image_inversion.py <span style='color:#111;'> 361B </span>","children":null,"spread":false}],"spread":true},{"title":".idea","children":[{"title":"vcs.xml <span style='color:#111;'> 180B </span>","children":null,"spread":false},{"title":"misc.xml <span style='color:#111;'> 197B </span>","children":null,"spread":false},{"title":"digtal-image-processing.iml <span style='color:#111;'> 329B </span>","children":null,"spread":false},{"title":"inspectionProfiles","children":[{"title":"Project_Default.xml <span style='color:#111;'> 1.75KB </span>","children":null,"spread":false},{"title":"profiles_settings.xml <span style='color:#111;'> 174B </span>","children":null,"spread":false}],"spread":true},{"title":"modules.xml <span style='color:#111;'> 298B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 47B </span>","children":null,"spread":false}],"spread":true},{"title":"img","children":[{"title":"2.2.jpg <span style='color:#111;'> 176.41KB </span>","children":null,"spread":false},{"title":"lena.jpg <span style='color:#111;'> 48.14KB </span>","children":null,"spread":false},{"title":"1.1.jpg <span style='color:#111;'> 16.98KB </span>","children":null,"spread":false},{"title":"3.1.jpg <span style='color:#111;'> 31.64KB </span>","children":null,"spread":false},{"title":"4.1.jpg <span style='color:#111;'> 75.36KB </span>","children":null,"spread":false},{"title":"1.2.jpg <span style='color:#111;'> 84.92KB </span>","children":null,"spread":false},{"title":"2.1.jpg <span style='color:#111;'> 5.03KB </span>","children":null,"spread":false},{"title":"1.3.jpg <span style='color:#111;'> 340.82KB </span>","children":null,"spread":false}],"spread":true},{"title":"3th","children":[{"title":"Image_sharpening.py <span style='color:#111;'> 3.46KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}]