Low light image fusion application

A typical result of taking picture using mobile device at low light condition is a dark image. If night mode available, often it would generate a blurry image. Most mobile applications solve this problem by mean of post-image processing—tuning and editing the dark image after capture. However, this...

Full description

Saved in:
Bibliographic Details
Main Author: Yonas Stephen Suhartono
Other Authors: School of Computer Engineering
Format: Final Year Project
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/59209
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-59209
record_format dspace
spelling sg-ntu-dr.10356-592092023-03-03T20:58:09Z Low light image fusion application Yonas Stephen Suhartono School of Computer Engineering Ramakrishna Kakarala DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision A typical result of taking picture using mobile device at low light condition is a dark image. If night mode available, often it would generate a blurry image. Most mobile applications solve this problem by mean of post-image processing—tuning and editing the dark image after capture. However, this method has a major setback; if an area in the image is highly saturated, tuning the image will not enhance the quality. Therefore, this project was aimed to build a low light photography application for iOS platform by mean of multi-exposure image fusion. There is no iOS application till present that uses multi-exposure image fusion technique for low light photography. Fusing the multi-exposure image can obtain the high SNR (signal-to-noise ratio) of a long exposure image and the sharpness of a short exposure image. As the result, pictures taken using this application will be brighter and have a well-balanced noise- to-sharpness ratio. Bachelor of Engineering (Computer Science) 2014-04-25T06:07:21Z 2014-04-25T06:07:21Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/59209 en Nanyang Technological University 76 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Yonas Stephen Suhartono
Low light image fusion application
description A typical result of taking picture using mobile device at low light condition is a dark image. If night mode available, often it would generate a blurry image. Most mobile applications solve this problem by mean of post-image processing—tuning and editing the dark image after capture. However, this method has a major setback; if an area in the image is highly saturated, tuning the image will not enhance the quality. Therefore, this project was aimed to build a low light photography application for iOS platform by mean of multi-exposure image fusion. There is no iOS application till present that uses multi-exposure image fusion technique for low light photography. Fusing the multi-exposure image can obtain the high SNR (signal-to-noise ratio) of a long exposure image and the sharpness of a short exposure image. As the result, pictures taken using this application will be brighter and have a well-balanced noise- to-sharpness ratio.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Yonas Stephen Suhartono
format Final Year Project
author Yonas Stephen Suhartono
author_sort Yonas Stephen Suhartono
title Low light image fusion application
title_short Low light image fusion application
title_full Low light image fusion application
title_fullStr Low light image fusion application
title_full_unstemmed Low light image fusion application
title_sort low light image fusion application
publishDate 2014
url http://hdl.handle.net/10356/59209
_version_ 1759855650493431808