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https://hdl.handle.net/10356/59209
Title: | Low light image fusion application | Authors: | Yonas Stephen Suhartono | Keywords: | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision | Issue Date: | 2014 | Abstract: | 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. | URI: | http://hdl.handle.net/10356/59209 | Schools: | School of Computer Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
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FYP Report Final - Yonas Stephen Suhartono (600dpi).pdf Restricted Access | Low Light Image Fusion Application (iOS) | 21.46 MB | Adobe PDF | View/Open |
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