Detection of quantization artifacts and its applications to transform encoder identification

Authors:
Weiqi Luo;Yuangen Wang;Jiwu Huang
Affiliations:
School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, China and Key Laboratory of Network Security and Cryptology, Fujian Normal University, Fuzhou, China;School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, China;School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, China and State Key Laboratory of Information Security, Institute of Software, Chinese Academy of Sciences, China
Venue:
IEEE Transactions on Information Forensics and Security
Year:
2010

Citing 4
Cited 1

Digital Image Processing

Digital Image Processing
Digital image source coder forensics via intrinsic fingerprints

IEEE Transactions on Information Forensics and Security
Exposing digital forgeries in color filter array interpolated images

IEEE Transactions on Signal Processing - Part II
A mathematical analysis of the DCT coefficient distributions for images

IEEE Transactions on Image Processing

Multimedia operator chain topology and ordering estimation based on detection and information theoretic tools

IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking

Quantified Score

Hi-index	0.00

Visualization

Abstract

Quantization is one of the commonly used techniques in most lossy image source encoders. It is observed that the quantization operation usually introduces some obvious artifacts into the histogram of the corresponding transform coefficients under various compression schemes. By investigating such inherent artifacts over all candidate transform coefficients, it is possible to identify the transform, as well as some parameters previously employed in the transform-based encoder from a decompressed image. In this paper, we first analyze the properties of the quantized coefficients and present a simple yet effective way to detect the quantization artifacts, and then we propose an approach to identify the transform-based encoder based on the quantization artifacts detection. The simulation results evaluated on thousands of natural images with some popular compression schemes demonstrate the effectiveness of our method.