Maria Paula Queluz

No-reference image quality assessment based on DCT domain statistics

This paper proposes a no-reference quality assessment metric for images subject to quantization noise in block-based DCT (discrete cosine transform) domain, as those resulting from JPEG or MPEG encoding. The proposed method is based on natural scene statistics of the DCT coefficients, whose distribution is usually modeled by a Laplace probability density function, with parameter @l. A new method for @l estimation from quantized coefficient data is presented; it combines maximum-likelihood with linear prediction estimates, exploring the correlation between @l values at adjacent DCT frequencies. The resulting coefficient distributions are then used for estimating the local error due to lossy encoding. Local error estimates are also perceptually weighted, using a well-known perceptual model by Watson. When confronted with subjective quality evaluation data, results show that the quality scores that result from the proposed algorithm are well correlated with the human perception of quality. Since no knowledge about the original (reference) images is required, the proposed method resembles a no-reference quality metric for image evaluation.

No-Reference Quality Assessment of H.264/AVC Encoded Video

This paper proposes a no-reference quality assessment metric for digital video subject to H.264/advanced video coding encoding. The proposed metric comprises two main steps: coding error estimation and perceptual weighting of this error. Error estimates are computed in the transform domain, assuming that discrete cosine transform (DCT) coefficients are corrupted by quantization noise. The DCT coefficient distributions are modeled using Cauchy or Laplace probability density functions, whose parameterization is performed using the quantized coefficient data and quantization steps. Parameter estimation is based on a maximum-likelihood estimation method combined with linear prediction. The linear prediction scheme takes advantage of the correlation between parameter values at neighbor DCT spatial frequencies. As for the perceptual weighting module, it is based on a spatiotemporal contrast sensitivity function applied to the DCT domain that compensates image plane movement by considering the movements of the human eye, namely smooth pursuit, natural drift, and saccadic movements. The video related inputs for the perceptual model are the motion vectors and the frame rate, which are also extracted from the encoded video. Subjective video quality assessment tests have been carried out in order to validate the results of the metric. A set of 11 video sequences, spanning a wide range of content, have been encoded at different bitrates and the outcome was subject to quality evaluation. Results show that the quality scores computed by the proposed algorithm are well correlated with the mean opinion scores associated to the subjective assessment.

Content-based integrity protection of digital images

The increasing availability of digitally stored information and the development of new multimedia broadcasting services, has recently motivated research on copyright protection and authentication schemes for these services. Possible solutions range from low-level systems based upon header description associated with the bit-stream (labelling), up to high level, holographically inlayed, non-deletable systems (watermarking). This paper is focused on authentication, using the labeling approach; a generic framework is firstly presented and two specific methods are then proposed for the particular cases of still images and videos. The resistance of both methods to JPEG and MPEG2 compression, as well as its sensitivity to image manipulations, are evaluated.

Spatial watermark for image verification

The recent development of digital multimedia communications together with the intrinsic capability of digital information to be copied and manipulated requires new copyright protection and content authentication schemes to be developed. This paper is devoted to the second issue, the one of image or video content authentication. A computationally efficient spatial watermarking technique for authentication of visual information, robust to small distortions caused by compression, is described. In essence, a content-dependent authentication data is embedded into the picture, by modifying the relationship of image projections throughout the entire image. To obtain a secure data embedding and extraction procedure, directions onto which image parts are projected depend on a secret key. In order to guarantee minimum visibility of the embedded data, the insertion process is used in conjunction with perceptual models, exploiting spatial domain masking effects. The viability of the method as a means for protecting the content is assessed under JPEG compression and semantic content modifications. With the present system, robustness to JPEG compression up to compression factors of about 1:10, can be achieved, maintaining the subjective image quality after watermark insertion. At the same time, it is possible to detect and localize small image manipulations.

A Novel Vehicular Mobility Model for Wireless Networks

In this paper a novel realistic vehicular mobility model is introduced. It captures the moving-in-groups, conscious traveling, and introduces the concept of smart traveling while following drivers’ social behavior extracted from inquiries and experimental traffic measurements. Under the model, a routing algorithm is considered. The routing algorithm minimizes the distance to a target on a step by step form, in every street crossing. This is done under a hierarchic street level structure that optimizes travel speed and quality. The mobility model was simulated and validated in a real mobility scenario using, as case study, the city of Lisbon. The correlation values (between simulated data and theoretical distributions), arrival to destination success rate and directional statistics produced satisfactory results. The model concept is perfectly generic and applicable to other locations, provided that the corresponding street database and vehicular traffic information are available. The model outputs several parameters, including sinuosity indicator and traffic load. The sinuosity indicator is a powerful parameter on the characterization of urban radio environments when mobility is used in wireless networks simulation. Vehicular traffic load analysis is also presented. It can be used in further work over wireless traffic modeling, on a street segment basis or on a AU (Analysis Unit) perspective.

Performance improvement of spatial watermarking through efficient nonbinary channel coding.

Many of the proposed image watermarking algorithms belong to the class of spread-spectrum techniques, in which a pseudo- noise signal (itself a function of the mark) is added to the host signal, either in space or frequency domains. Under these approaches, several results and concepts from digital communication theory, such as M-ary digital modulation, channel coding and optimum detection, are easily applicable.

A smart scheme for relay selection in cooperative wireless communication systems

The performance of multiple-input multiple-output systems using spatial multiplexing can be degraded when the spatial information channels are correlated. This work proposes a solution to this problem, which is based on a cooperative wireless communication system. Within the cooperative system, the relay is selected either randomly or using the smart selection scheme, a simple and distributed approach proposed herein. These relay selection schemes are evaluated for several situations within a small cell environment, using a simulator that generates frequency-selective channel realizations. The simulation results show that the smart selection scheme yields high capacity gains close to the theoretical maximum gain.

MIMO channel capacity spatial distribution in a microcell environment

In this paper the spatial distribution of the channel capacity of Multiple Input Multiple Output (MIMO) wireless systems within a microcell scenario is studied. Based on the capacity location dependency, made clear by realistic simulation results, a segmentation of the cell area into high and low capacity regions is proposed. The Base Station (BS) and Mobile Stations (MSs) inter-antenna spacing impact on these regions is also investigated. The results suggest the most efficient ways to enlarge the high capacity region, providing a framework to optimize the design and deployment of MIMO systems.

Signal combining techniques for video watermarking extraction

This paper analyses the effect of signal combining techniques in video watermark extraction. A spread-spectrum like discrete cosine transform domain (DCT domain) watermarking technique is used as embedding method, together with common error correction codes (BCH, Reed-Solomon with multilevel signaling, and binary convolutional codes with Viterbi decoding). Besides an analytical evaluation of the signal combining strategies, its effectiveness is also assessed experimentally under MPEG-2 video compression.

Diversity Enhancement of Coded Spread Spectrum Video Watermarking

This paper analyses the effect of signal combination techniques in videowatermark detection. A spatial spread spectrum based watermarking techique isused as embedding method, in combination with common error correction codes(BCH, Reed-Solomon with multilevel signaling, binary convolutional codes withViterbi decoding). Besides an analytical evaluation of the bit error rate, theeffectiveness of the channel coding and diversity techniques is also assessedexperimentally under MPEG-2 video compression.