Abstract
Image colorization is the procedure of adding RGB color space value to the original greyscale image. Greyscale Image carries only the intensity information at each pixel value. This intensity mostly varies from 0 to 256 which is just enough to observe a gradual change in intensity. Image colorization is a very crucial process and has many benefits of its own for example in medical science, the entertainment industry, and the study of scientific and astrological images etc. We have developed a CNN model in which we designed our own CNN layers that takes a greyscale image as input and returns a colored image as output. The model proposed here does not require any human interaction in the process of colorization of the image once it is fed to the neural network.
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