Improving source camera identification using a simplified total variation based noise removal algorithm

In this paper a new method for photo-response non-uniformity (PRNU) noise extraction is proposed. Photo-response non-uniformity noise patterns are a reliably method for digital camera identification. Especially with a large number of images the process of camera identification can be time consuming. The proposed method aims to increase the speed of PRNU extraction without losing accuracy when compared to the state-of-the-art method. Currently wavelet based denoising is used as the standard for PRNU extraction. Our proposed method is based on a simplified version of the Total Variation based noise removal algorithm. Results show that extraction is about 3.5 times faster with our method than with the wavelet based denoising algorithm. While initially only an increase in speed was the goal, results indicate that the Total Variation based noise removal algorithm is not only faster, but also more accurate than the state-of-the-art method.