Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/38835
Title: A new in-camera color imaging model for computer vision
Authors: LIN HAITING
Keywords: radiometric calibration, in-camera image processing, gamut mapping, white balance
Issue Date: 22-Jan-2013
Source: LIN HAITING (2013-01-22). A new in-camera color imaging model for computer vision. ScholarBank@NUS Repository.
Abstract: We present a study of the in-camera image processing through an extensive analysis of images from over 30 cameras. Our goal is to investigate if image values can be transformed to physically meaningful values, and if so, when and how this can be done. From our analysis, we found a major limitation of the imaging model employed in conventional radiometric calibration methods and propose a new in-camera imaging model that fits well with today?s cameras. We also present associated calibration procedures that allow us to convert sRGB images back to their original RAW responses in a manner that is significantly more accurate than any existing methods. Additionally, we show how our model can be used to build an image correction application that converts a sRGB input image captured with the wrong settings to a sRGB output image that would have been recorded under the correct settings of a specific camera.
URI: http://scholarbank.nus.edu.sg/handle/10635/38835
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
LinHT.pdf28.79 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

168
checked on Dec 18, 2017

Download(s)

642
checked on Dec 18, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.