Conference proceeding
FORENSIC ESTIMATION AND RECONSTRUCTION OF A CONTRAST ENHANCEMENT MAPPING
2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, pp 1698-1701
01 Jan 2010
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Due to the ease with which convincing digital image forgeries can be created, a need has arisen for digital forensic techniques capable of detecting image manipulation. Once image alterations have been identified, the next logical forensic task is to recover as much information as possible about the unaltered version of image and the operation used to modify it. Previous work has dealt with the forensic detection of contrast enhancement in digital images. In this paper we propose an iterative algorithm to jointly estimate any arbitrary contrast enhancement mapping used to modify an image as well as the pixel value histogram of the image before contrast enhancement. To do this, we use a probabilistic model of an image's pixel value histogram to determine which histogram entries are most likely to correspond to contrast enhancement artifacts. Experimental results are presented to demonstrate the effectiveness of our proposed method.
Metrics
Details
- Title
- FORENSIC ESTIMATION AND RECONSTRUCTION OF A CONTRAST ENHANCEMENT MAPPING
- Creators
- Matthew C. Stamm - University of Maryland, College ParkK. J. Ray Liu - University of Maryland, College ParkIEEE
- Publication Details
- 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, pp 1698-1701
- Series
- International Conference on Acoustics Speech and Signal Processing ICASSP
- Publisher
- IEEE
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000287096001171
- Scopus ID
- 2-s2.0-78049407658
- Other Identifier
- 991019295311904721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Acoustics
- Computer Science, Theory & Methods
- Engineering, Electrical & Electronic