This paper proposes a high-definition video watermarking method robust against compound geometrical attacks by camcorder capture as well as common video processing such as frame-rate conversion and transcoding. Unlike traditional watermarking systems using the original reference pattern, the proposed method exploits the reference pattern estimated from the watermarked video. Since the reference pattern and watermark pattern are embedded in the same spatial position of each frame, the two patterns estimated from the embedded video are always in spatial sync. Thus, the watermark information can be simply detected without an additional synchronizing step, even if geometrical distortions happen to the marked video. Also, the problem of misestimation of the reference pattern caused by temporal video clipping is solved using the proposed two-pass detector. Extensive experiments prove that the proposed method is robust against various temporal and spatial distortions.
We propose a steganalysis defeating the steganographic method using pixel-value differencing and modulus function, which is a recent method with high security and capacity for secret communication. The presented steganalysis is designed to reveal the existence of the message and uses three steganalytic measures that remarkably increase their values in the stego images. Hence, the stego images are statistically separated with the cover images. Detection of the hidden message is possible by modeling the changes generated by the embedding process and comparing the values of the steganalytic measures. To increase the performance of the steganalytic measures, a novel histogram estimation scheme is used to estimate the histogram value of the cover image and the embedding ratio. A support vector machine classifier is adopted to discriminate between cover and stego images. The experimental results verify that the proposed steganalysis can detect the stego images with 97.1% accuracy, even though the embedding ratio is just 10% of the maximum hiding capacity. Also, the length of the hidden message can be successfully estimated without the cover image.
An autocorrelation function (ACF) to synchronize watermarks has been adopted in practical applications because of its robustness against affine transforms. However, ACFs are vulnerable to projective transform, which commonly occurs during the illegal copying of cinema footage due to the angle of the camcorder relative to the screen. The cinema footage that is captured by camcorders both is projected and has undergone digital-to-analog and analog-to-digital conversion (D-A/A-D conversion). We present a novel watermarking scheme that uses a local autocorrelation function (LACF) that can resist projective transforms as well as affine transforms. A watermark also used for synchronization is designed and additively embedded in the spatial domain. The embedded watermark is extracted in a blind way after recovering from distortions. The LACF scheme with a mathematical model is proposed to synchronize the watermark against distortions. On various video clips, experimental results show that the presented scheme is robust against projective distortions as well as D-A/A-D conversion.
In this paper, we present an image compression algorithm that is capable of significantly reducing the vast amount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet transform to remove the spatial redundancy. The transformed images are then encoded by Hilbert-curve scanning and run-length-encoding, followed by Huffman coding. We also present the performance of the proposed algorithm with the LANDSAT multispectral scanner data. The loss of information is evaluated by PSNR (peak signal to noise ratio) and classification capability.