Please use this identifier to cite or link to this item: 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
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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