Color transfer between images

Image processing has emerged as an important topic in computer vision, enabling a wide range of applications such as image improvement, object detection, and artistic alterations. Color transfer is a fascinating feature of image processing that includes altering the color appearance of an image whil...

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Main Author: Gee, Brielle Zi En
Other Authors: He Ying
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175345
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1753452024-04-26T15:44:53Z Color transfer between images Gee, Brielle Zi En He Ying School of Computer Science and Engineering YHe@ntu.edu.sg Computer and Information Science Engineering Image processing has emerged as an important topic in computer vision, enabling a wide range of applications such as image improvement, object detection, and artistic alterations. Color transfer is a fascinating feature of image processing that includes altering the color appearance of an image while keeping its underlying content. Color transfer enhances the creative and aesthetic aspects of image alterations by providing tools for photographers, designers and artists to express their emotions and tell stories through images. The report will be focusing on a comparative analysis of two popular color transfer algorithms: the Reinhard algorithm [1] and the N-Dimensional Probability Color Transfer technique [2]. The usage of image histogram and color clouds provides a quantitative and visual technique to objectively compare the performance of each color transfer algorithm. Furthermore, several other algorithms will be introduced, which includes using Fully Convolutional Networks for Semantic Segmentation [3],to provide further insights on the topic of color transfer. Bachelor's degree 2024-04-23T12:12:00Z 2024-04-23T12:12:00Z 2024 Final Year Project (FYP) Gee, B. Z. E. (2024). Color transfer between images. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175345 https://hdl.handle.net/10356/175345 en SCSE23-0342 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
Engineering
spellingShingle Computer and Information Science
Engineering
Gee, Brielle Zi En
Color transfer between images
description Image processing has emerged as an important topic in computer vision, enabling a wide range of applications such as image improvement, object detection, and artistic alterations. Color transfer is a fascinating feature of image processing that includes altering the color appearance of an image while keeping its underlying content. Color transfer enhances the creative and aesthetic aspects of image alterations by providing tools for photographers, designers and artists to express their emotions and tell stories through images. The report will be focusing on a comparative analysis of two popular color transfer algorithms: the Reinhard algorithm [1] and the N-Dimensional Probability Color Transfer technique [2]. The usage of image histogram and color clouds provides a quantitative and visual technique to objectively compare the performance of each color transfer algorithm. Furthermore, several other algorithms will be introduced, which includes using Fully Convolutional Networks for Semantic Segmentation [3],to provide further insights on the topic of color transfer.
author2 He Ying
author_facet He Ying
Gee, Brielle Zi En
format Final Year Project
author Gee, Brielle Zi En
author_sort Gee, Brielle Zi En
title Color transfer between images
title_short Color transfer between images
title_full Color transfer between images
title_fullStr Color transfer between images
title_full_unstemmed Color transfer between images
title_sort color transfer between images
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175345
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