基于核回归 Kernel regression 的图像处理作者Takeda的matlab代码 应用于去噪 超分 去模糊等等

[{"title":"（ 27 个子文件 270KB ） 基于核回归 Kernel regression 的图像处理作者Takeda的matlab代码 应用于去噪 超分 去模糊等等","children":[{"title":"KernelRegressionBasedImageProcessingToolBox_ver1-2beta","children":[{"title":"Examples","children":[{"title":"Lena_upscale.m <span style='color:#111;'> 1.09KB </span>","children":null,"spread":false},{"title":"Lena_denoise.m <span style='color:#111;'> 1.81KB </span>","children":null,"spread":false},{"title":"Lena_irregular.m <span style='color:#111;'> 1.50KB </span>","children":null,"spread":false},{"title":"Lena_saltpepper.m <span style='color:#111;'> 2.74KB </span>","children":null,"spread":false},{"title":"JFK_denoise.m <span style='color:#111;'> 2.16KB </span>","children":null,"spread":false},{"title":"Pepper_deblock.m <span style='color:#111;'> 1.81KB </span>","children":null,"spread":false}],"spread":true},{"title":"SupportFunctions","children":[{"title":"mymse.m <span style='color:#111;'> 57B </span>","children":null,"spread":false},{"title":"round0_255.m <span style='color:#111;'> 149B </span>","children":null,"spread":false},{"title":"upsample2.m <span style='color:#111;'> 273B </span>","children":null,"spread":false},{"title":"RGB2YCC.m <span style='color:#111;'> 475B </span>","children":null,"spread":false},{"title":"EdgeMirror.m <span style='color:#111;'> 406B </span>","children":null,"spread":false},{"title":"YCC2RGB.m <span style='color:#111;'> 340B </span>","children":null,"spread":false},{"title":"downsample2.m <span style='color:#111;'> 246B </span>","children":null,"spread":false}],"spread":true},{"title":"TestImages","children":[{"title":"pepper.bmp <span style='color:#111;'> 64.55KB </span>","children":null,"spread":false},{"title":"JFKreg.jpg <span style='color:#111;'> 40.46KB </span>","children":null,"spread":false},{"title":"pepper.jpg <span style='color:#111;'> 2.82KB </span>","children":null,"spread":false},{"title":"lena.png <span style='color:#111;'> 147.66KB </span>","children":null,"spread":false}],"spread":true},{"title":"KernelRegression","children":[{"title":"skr0_regular.m <span style='color:#111;'> 2.69KB </span>","children":null,"spread":false},{"title":"steering.m <span style='color:#111;'> 1.35KB </span>","children":null,"spread":false},{"title":"ckr2L1_regular.m <span style='color:#111;'> 2.58KB </span>","children":null,"spread":false},{"title":"ckr2all_regular.m <span style='color:#111;'> 2.35KB </span>","children":null,"spread":false},{"title":"skr2L1_regular.m <span style='color:#111;'> 3.49KB </span>","children":null,"spread":false},{"title":"skr2_irregular.m <span style='color:#111;'> 2.99KB </span>","children":null,"spread":false},{"title":"ckr2_irregular.m <span style='color:#111;'> 2.09KB </span>","children":null,"spread":false},{"title":"ckr2_regular.m <span style='color:#111;'> 2.40KB </span>","children":null,"spread":false},{"title":"skr2_regular.m <span style='color:#111;'> 3.25KB </span>","children":null,"spread":false},{"title":"skr0_irregular.m <span style='color:#111;'> 2.55KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}]