{"id":842,"date":"2018-09-01T02:45:26","date_gmt":"2018-09-01T02:45:26","guid":{"rendered":"http:\/\/muthu.co\/?p=842"},"modified":"2021-05-24T03:04:14","modified_gmt":"2021-05-24T03:04:14","slug":"converting-color-images-to-grayscale-using-numpy-and-some-mathematics","status":"publish","type":"post","link":"http:\/\/write.muthu.co\/converting-color-images-to-grayscale-using-numpy-and-some-mathematics\/","title":{"rendered":"Converting Color Images to Grayscale using numpy and some Mathematics"},"content":{"rendered":"\n
An extremely magnified image at the end is just blocks of colors called pixels, where each pixel is formed by the combination of Red, Blue and Green, our primary colors. RGB color space or RGB color system<\/a>, constructs all the colors from the combination of the intensities of Red, Green and Blue colors.<\/p>\n\n\n\n The red, green and blue use 8 bits each, which have integer values from 0 to 255. This makes 256*256*256=16777216 possible colors. Below is a chart of basic colors.<\/p>\n\n\n\n<\/a><\/figure><\/div>\n\n\n\n