Revealing the Trace of High-Quality JPEG Compression Through Quantization Noise Analysis
Abstract of Revealing the Trace of High-Quality JPEG Compression
Revealing the Trace of High-Quality JPEG Compression Through Quantization Noise Analysis,To identify whether an image has been JPEG compressed is an important issue in forensic practice. The state-of-the-art methods fail to identify high-quality compressed images, which are common on the Internet. In this paper, we provide a novel quantization noise-based solution to reveal the traces of JPEG compression. Based on the analysis of noises in multiple-cycle JPEG compression, we define a quantity called forward quantization noise. We analytically derive that a decompressed JPEG image has a lower variance of forward quantization noise than its uncompressed counterpart. With the conclusion, we develop a simple yet very effective detection algorithm to identify decompressed JPEG images. We show that our method outperforms the state-of-the-art methods by a large margin especially for high-quality compressed images through extensive experiments on various sources of images. We also demonstrate that the proposed method is robust to small image size and chroma subsampling. The proposed algorithm can be applied in some practical applications, such as Internet image classification and forgery detection.
Conclusion
In this Revealing the Trace of High-Quality JPEG Compression Through Quantization Noise Analysis paper, we propose a method to reveal the traces of JPEG compression. The proposed method is based on analyzing the forward quantization noise, which is obtained by quantizing the block-DCT coefficients with a step of one. A decompressed JPEG image has a lower noise variance than its uncompressed counterpart. Such an observation can be derived analytically. The main contribution of this work is to address the challenges posed by high-quality compression in JPEG compression identification. Specifically, our method is able to detect the images previously compressed with IJG QF=99 or 100, and Photoshop QF from 90 to 100. Experiments show that high-quality compressed images are common on the Internet, and our method is effective to identify them. Besides, our method is robust to small image size and color sub-sampling in chrominance channels.