An efficient Convolutional Neural Network (CNN) Based Image Colorization Technique

Abstract

Color in any image playing a vital role for better understanding and real image visualization. In past when there was no concept of colored images each black and white image need to highlight its own merits to explain an image in a better way, but when the concept of colored images started the things were totally changed to describe and highlight key features and attributes of an image in a more better and effective manner. The key issue is that the old images and videos are color less and in some cases it needs to be colorized. There are a number of applications are uses to colorized a gray-scale image. The authors of this paper also presented an efficient deep learning based image colorization technique. The proposed system maps all the gray contrast pixels of the image into its corresponding colored pixels to produce a colored image using Convolutional Neural Network (CNN) technique. The proposed system is totally an automated system and it avoid any manual work or user hand-define rules. The system first read the gray contrast of each pixel of image; matches function then create the corresponding color contrast from the color map and finally convert the gray contrast image into color image. The system tested around 100 images and found accuracy about 95%.