Turning Diffusion Based Image Colorization Into Efficient Color Compression

Dr. Mohammed Abdul Waheed; Syed Yunus

Title:
Turning Diffusion Based Image Colorization Into Efficient Color Compression

Authors:
Syed Yunus | Dr. Mohammed Abdul Waheed
DOI:
https://doi.org/10.31142/ijtsrd18184

Cite This Article :

Syed Yunus | Dr. Mohammed Abdul Waheed "Turning Diffusion Based Image Colorization Into Efficient Color Compression" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5, August 2018, pp.1842-1844, URL: https://www.ijtsrd.com/papers/ijtsrd18184.pdf

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Abstract :
Neigh-boring pixels with comparable gray-values likewise have comparative hues. In the first place they change the picture to YUV space to acquire a arrangement shading decay. At that point they limit the distinction of every obscure shading pixel in YUV space to a biased normal of its 3 × 3 neighbor-hood. Then this undertaking is tedious and dull, analysts go for limiting the measure of client communication that is required while as yet enabling craftsmen to impact the outcome. The technique for Levin et al is a traditional separate replica for knock oriented colorization there the client recommends a couple of shading writes and the calculation fills in the absent hues. In picture pressure, at first look a disconnected field, dispersion oriented codec’s seek after comparable thoughts. There are likewise different non-neighborhood approaches for colorization: They have the favorable position that they can proliferate shading all around to all picture territories that have comparable structure.

Keywords :
all picture territories that have comparable structure.

Publication Details:

Unique Identification Number : IJTSRD18184

Published In : Volume-2 | Issue-5, August 2018

Page Number(s) : 1842-1844

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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