Source Camera Identification With Dual-Tree Complex Wavelet Transform

Sensor pattern noise (SPN) extraction is a critical stage of the sensor based source camera identification (SCI). However, the quality of the extracted SPN with the traditional discrete wavelet transform (DWT) based method is poor around strong edges and along with the image border. To fill this gap...

Full description

Bibliographic Details
Main Authors: Hui Zeng, Yongcai Wan, Kang Deng, Anjie Peng
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8966247/
id doaj-777cd3860bcd42a4a94eb19a6993c705
record_format Article
spelling doaj-777cd3860bcd42a4a94eb19a6993c7052021-03-30T02:55:19ZengIEEEIEEE Access2169-35362020-01-018188741888310.1109/ACCESS.2020.29688558966247Source Camera Identification With Dual-Tree Complex Wavelet TransformHui Zeng0https://orcid.org/0000-0002-3776-4309Yongcai Wan1https://orcid.org/0000-0002-6661-4676Kang Deng2https://orcid.org/0000-0002-9734-0137Anjie Peng3https://orcid.org/0000-0001-9287-7536School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, ChinaSchool of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, ChinaSchool of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, ChinaSchool of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, ChinaSensor pattern noise (SPN) extraction is a critical stage of the sensor based source camera identification (SCI). However, the quality of the extracted SPN with the traditional discrete wavelet transform (DWT) based method is poor around strong edges and along with the image border. To fill this gap, we propose a dual tree complex wavelet transform (DTCWT) based method to extract the SPN from a given image, which achieves better performance in the area around strong edges. Furthermore, symmetric boundary extension instead of the periodized boundary extension is used for enhancing the quality of SPN along with the image border. Extensive experimental results on both synthetic noisy images and real-world photographs clearly demonstrate the superior SCI performance of the proposed method over state-of-the-arts. Moreover, the proposed method also shows potential in the application of image tampering localization.https://ieeexplore.ieee.org/document/8966247/Sensor pattern noisesource camera identificationdiscrete wavelet transformdual tree complex wavelet transform
collection DOAJ
language English
format Article
sources DOAJ
author Hui Zeng
Yongcai Wan
Kang Deng
Anjie Peng
spellingShingle Hui Zeng
Yongcai Wan
Kang Deng
Anjie Peng
Source Camera Identification With Dual-Tree Complex Wavelet Transform
IEEE Access
Sensor pattern noise
source camera identification
discrete wavelet transform
dual tree complex wavelet transform
author_facet Hui Zeng
Yongcai Wan
Kang Deng
Anjie Peng
author_sort Hui Zeng
title Source Camera Identification With Dual-Tree Complex Wavelet Transform
title_short Source Camera Identification With Dual-Tree Complex Wavelet Transform
title_full Source Camera Identification With Dual-Tree Complex Wavelet Transform
title_fullStr Source Camera Identification With Dual-Tree Complex Wavelet Transform
title_full_unstemmed Source Camera Identification With Dual-Tree Complex Wavelet Transform
title_sort source camera identification with dual-tree complex wavelet transform
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Sensor pattern noise (SPN) extraction is a critical stage of the sensor based source camera identification (SCI). However, the quality of the extracted SPN with the traditional discrete wavelet transform (DWT) based method is poor around strong edges and along with the image border. To fill this gap, we propose a dual tree complex wavelet transform (DTCWT) based method to extract the SPN from a given image, which achieves better performance in the area around strong edges. Furthermore, symmetric boundary extension instead of the periodized boundary extension is used for enhancing the quality of SPN along with the image border. Extensive experimental results on both synthetic noisy images and real-world photographs clearly demonstrate the superior SCI performance of the proposed method over state-of-the-arts. Moreover, the proposed method also shows potential in the application of image tampering localization.
topic Sensor pattern noise
source camera identification
discrete wavelet transform
dual tree complex wavelet transform
url https://ieeexplore.ieee.org/document/8966247/
work_keys_str_mv AT huizeng sourcecameraidentificationwithdualtreecomplexwavelettransform
AT yongcaiwan sourcecameraidentificationwithdualtreecomplexwavelettransform
AT kangdeng sourcecameraidentificationwithdualtreecomplexwavelettransform
AT anjiepeng sourcecameraidentificationwithdualtreecomplexwavelettransform
_version_ 1724184308867923968