Grey level to RGB using YCbCr color space Technique
Author(s) -
R. Bhuvana Vijaya,
K. Prudvi,
Logesh Ravi,
M. Jogendra
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016911180
Subject(s) - grayscale , computer science , artificial intelligence , computer vision , ycbcr , rgb color model , color space , color image , color depth , monochrome , color histogram , color balance , computer graphics (images) , pixel , lightness , false color , image processing , image (mathematics)
Converting color images to grayscale is used for various reasons, like for reproducing on monochrome devices, subsequent processing. Each pixel in color image is described by a triple (R, G, B) of intensities like red, green, and blue. But how do you map that to a single value i.e. grayscale value. There are three methods to convert it. Average, Luminosity, Lightness. Different color models are used for different applications such as computer graphics, image processing, TV broadcasting, and computer vision. But still now there is no particular method for converting of grayscale to color image. In this paper a new approach was introduce to convert the grayscale image to color by using an YCbCr color space technique. Simulation results are presented to show how this approach is used to convert the grayscale to color image.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom