Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Integrated noise modeling for image sensor using bayer domain images

Authors
Baek, Yeul-MinKim, Joong-GeunCho, Dong-ChanLee, Jin-AeonKim, Whoi Yul
Issue Date
May-2009
Publisher
SPRINGER
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.5496 LNCS, pp.413 - 424
Indexed
SCOPUS
Journal Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
5496 LNCS
Start Page
413
End Page
424
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/176802
DOI
10.1007/978-3-642-01811-4_37
ISSN
0302-9743
Abstract
Most of image processing algorithms assume that an image has an additive white Gaussian noise (AWGN). However, since the real noise is not AWGN, such algorithms are not effective with real images acquired by image sensors for digital camera. In this paper, we present an integrated noise model for image sensors that can handle shot noise, dark-current noise and fixedpattern noise together. In addition, unlike most noise modeling methods, parameters for the model do not need to be re-configured depending on input images once it is made. Thus the proposed noise model is best suitable for various imaging devices. We introduce two applications of our noise model: edge detection and noise reduction in image sensors. The experimental results show how effective our noise model is for both applications.
Files in This Item
Go to Link
Appears in
Collections
서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles

qrcode

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

Altmetrics

Total Views & Downloads

BROWSE