A study of probability distributions of DCT coefficients in JPEG compression

The Discrete Cosine Transform (DCT) used in JPEG compression has shown excellent energy compaction properties that rival that of the ideal Karhunen-Loève Transform. Lossy compression in JPEG is achieved by distorting 8x8 block DCT coefficients through quantization. It has been shown in literature that DC block DCT coefficients are Gaussian probability distributed and AC block DCT coefficients are Generalized Normal probability distributed. In this investigation, three probability density models for individual modes of non- quantized AC block DCT coefficients are evaluated and are used as basis for the derivation of probability distributions for quantized block DCT coefficients. The suitability of each of the three derived models is evaluated using the Kolmogorov-Smirnov and χ2 goodness-of-fit tests, and the moments of the best-fit model are derived. The best-fit model is applied to detect the presence and extent of JPEG compression history in bitmap images. A model for all quantized AC block DCT coefficients is derived using mixtures of individual quantized block DCT modes, and the model hence developed is used to validate the Generalized Benford\u27s Law for leading digit distributions of quantized AC block DCT coefficients

Spread spectrum-based video watermarking algorithms for copyright protection

Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen

Oxygen minimum zone: An important oceanographic habitat for deep-diving northern elephant seals, Mirounga angustirostris.

Little is known about the foraging behavior of top predators in the deep mesopelagic ocean. Elephant seals dive to the deep biota-poor oxygen minimum zone (OMZ) (>800 m depth) despite high diving costs in terms of energy and time, but how they successfully forage in the OMZ remains largely unknown. Assessment of their feeding rate is the key to understanding their foraging behavior, but this has been challenging. Here, we assessed the feeding rate of 14 female northern elephant seals determined by jaw motion events (JME) and dive cycle time to examine how feeding rates varied with dive depth, particularly in the OMZ. We also obtained video footage from seal-mounted videos to understand their feeding in the OMZ. While the diel vertical migration pattern was apparent for most depths of the JME, some very deep dives, beyond the normal diel depth ranges, occurred episodically during daylight hours. The midmesopelagic zone was the main foraging zone for all seals. Larger seals tended to show smaller numbers of JME and lower feeding rates than smaller seals during migration, suggesting that larger seals tended to feed on larger prey to satisfy their metabolic needs. Larger seals also dived frequently to the deep OMZ, possibly because of a greater diving ability than smaller seals, suggesting their dependency on food in the deeper depth zones. Video observations showed that seals encountered the rarely reported ragfish (Icosteus aenigmaticus) in the depths of the OMZ, which failed to show an escape response from the seals, suggesting that low oxygen concentrations might reduce prey mobility. Less mobile prey in OMZ would enhance the efficiency of foraging in this zone, especially for large seals that can dive deeper and longer. We suggest that the OMZ plays an important role in structuring the mesopelagic ecosystem and for the survival and evolution of elephant seals

Real-time detection and tracking of multiple objects with partial decoding in H.264/AVC bitstream domain

In this paper, we show that we can apply probabilistic spatiotemporal macroblock filtering (PSMF) and partial decoding processes to effectively detect and track multiple objects in real time in H.264|AVC bitstreams with stationary background. Our contribution is that our method cannot only show fast processing time but also handle multiple moving objects that are articulated, changing in size or internally have monotonous color, even though they contain a chaotic set of non-homogeneous motion vectors inside. In addition, our partial decoding process for H.264|AVC bitstreams enables to improve the accuracy of object trajectories and overcome long occlusion by using extracted color information.Comment: SPIE Real-Time Image and Video Processing Conference 200

A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model

To train Variational Autoencoders (VAEs) to generate realistic imagery requires a loss function that reflects human perception of image similarity. We propose such a loss function based on Watson's perceptual model, which computes a weighted distance in frequency space and accounts for luminance and contrast masking. We extend the model to color images, increase its robustness to translation by using the Fourier Transform, remove artifacts due to splitting the image into blocks, and make it differentiable. In experiments, VAEs trained with the new loss function generated realistic, high-quality image samples. Compared to using the Euclidean distance and the Structural Similarity Index, the images were less blurry; compared to deep neural network based losses, the new approach required less computational resources and generated images with less artifacts.Comment: Published at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020

You Owe Me

In business and politics, gifts are often aimed at influencing the recipient at the expense of third parties. In an experimental study, which removes informational and incentive confounds, subjects strongly respond to small gifts even though they understand the gift giver’s intention. Our findings question existing models of social preferences. They point to anthropological and sociological theories about gifts creating an obligation to reciprocate. We capture these effects in a simple extension of existing models. We show that common policy responses (disclosure, size limits) may be ineffective, consistent with our model. Financial incentives are effective but can backfire

Growth mixture modeling as an exploratory analysis tool in longitudinal quantitative trait loci analysis

We examined the properties of growth mixture modeling in finding longitudinal quantitative trait loci in a genome-wide association study. Two software packages are commonly used in these analyses: Mplus and the SAS TRAJ procedure. We analyzed the 200 replicates of the simulated data with these programs using three tests: the likelihood-ratio test statistic, a direct test of genetic model coefficients, and the chi-square test classifying subjects based on the trajectory model's posterior Bayesian probability. The Mplus program was not effective in this application due to its computational demands. The distributions of these tests applied to genes not related to the trait were sensitive to departures from Hardy-Weinberg equilibrium. The likelihood-ratio test statistic was not usable in this application because its distribution was far from the expected asymptotic distributions when applied to markers with no genetic relation to the quantitative trait. The other two tests were satisfactory. Power was still substantial when we used markers near the gene rather than the gene itself. That is, growth mixture modeling may be useful in genome-wide association studies. For markers near the actual gene, there was somewhat greater power for the direct test of the coefficients and lesser power for the posterior Bayesian probability chi-square test