Frederic Dufaux

A no-reference perceptual blur metric

We present a no-reference blur metric for images and video. The blur metric is based on the analysis of the spread of the edges in an image. Its perceptual significance is validated through subjective experiments. The novel metric is near real-time, has low computational complexity and is shown to perform well over a range of image content. Potential applications include optimization of source coding, network resource management and autofocus of an image capturing device.

Motion estimation techniques for digital TV: a review and a new contribution

The key to high performance in image sequence coding lies in an efficient reduction of the temporal redundancies. For this purpose, motion estimation and compensation techniques have been successfully applied. This paper studies motion estimation algorithms in the context of first generation coding techniques commonly used in digital TV. In this framework, estimating the motion in the scene is not an intrinsic goal. Motion estimation should indeed provide good temporal prediction and simultaneously require low overhead information. More specifically the aim is to minimize globally the bandwidth corresponding to both the prediction error information and the motion parameters. This paper first clarifies the notion of motion, reviews classical motion estimation techniques, and outlines new perspectives. Block matching techniques are shown to be the most appropriate in the framework of first generation coding. To overcome the drawbacks characteristic of most block matching techniques, this paper proposes a new locally adaptive multigrid block matching motion estimation technique. This algorithm has been designed taking into account the above aims. It leads to a robust motion field estimation precise prediction along moving edges and a decreased amount of side information in uniform areas. Furthermore, the algorithm controls the accuracy of the motion estimation procedure in order to optimally balance the amount of information corresponding to the prediction error and to the motion parameters. Experimental results show that the technique results in greatly enhanced visual quality and significant saving in terms of bit rate when compared to classical block matching techniques. >

Perceptual Blur and Ringing Metrics: Application to JPEG2000

We present a full- and no-reference blur metric as well as a full-reference ringing metric. These metrics are based on an analysis of the edges and adjacent regions in an image and have very low computational complexity. As blur and ringing are typical artifacts of wavelet compression, the metrics are then applied to JPEG2000 coded images. Their perceptual significance is corroborated through a number of subjective experiments. The results show that the proposed metrics perform well over a wide range of image content and distortion levels. Potential applications include source coding optimization and network resource management.

Efficient, robust, and fast global motion estimation for video coding

In this paper, we propose an efficient, robust, and fast method for the estimation of global motion from image sequences. The method is generic in that it can accommodate various global motion models, from a simple translation to an eight-parameter perspective model. The algorithm is hierarchical and consists of three stages. In the first stage, a low-pass image pyramid is built. Then, an initial translation is estimated with full-pixel precision at the top of the pyramid using a modified n-step search matching. In the third stage, a gradient descent is executed at each level of the pyramid starting from the initial translation at the coarsest level. Due to the coarse initial estimation and the hierarchical implementation, the method is very fast. To increase robustness to outliers, we replace the usual formulation based on a quadratic error criterion with a truncated quadratic function. We have applied the algorithm to various test sequences within an MPEG-4 coding system. From the experimental results we conclude that global motion estimation provides significant performance gains for video material with camera zoom and/or pan. The gains result from a reduced prediction error and a more compact representation of motion. We also conclude that the robust error criterion can introduce additional performance gains without increasing computational complexity.

Scrambling for Privacy Protection in Video Surveillance Systems

In this paper, we address the problem of privacy protection in video surveillance. We introduce two efficient approaches to conceal regions of interest (ROIs) based on transform-domain or codestream-domain scrambling. In the first technique, the sign of selected transform coefficients is pseudorandomly flipped during encoding. In the second method, some bits of the codestream are pseudorandomly inverted. We address more specifically the cases of MPEG-4 as it is today the prevailing standard in video surveillance equipment. Simulations show that both techniques successfully hide private data in ROIs while the scene remains comprehensible. Additionally, the amount of noise introduced by the scrambling process can be adjusted. Finally, the impact on coding efficiency performance is small, and the required computational complexity is negligible.

Scrambling for Video Surveillance with Privacy

In this paper, we address the problem of scrambling regions of interest in a video sequence for the purpose of preserving privacy in video surveillance. We propose an efficient solution based on transform-domain scrambling. More specifically, the sign of selected transform coefficients is pseudo-randomly flipped during encoding. We address more specifically the two cases of MPEG-4 and Motion JPEG 2000. Simulation results show that the technique can be successfully applied to conceal information in regions of interest in the scene while providing with a good level of security. Furthermore, the scrambling is flexible and allows adjusting the amount of distortion introduced. Finally, this is achieved with a small impact on coding performance and negligible computational complexity increase.

The JPEG XR image coding standard [Standards in a Nutshell]

JPEG XR is the newest image coding standard from the JPEG committee. It primarily targets the representation of continuous-tone still images such as photographic images and achieves high image quality, on par with JPEG 2000, while requiring low computational resources and storage capacity. Moreover, it effectively addresses the needs of emerging high dynamic range imagery applications by including support for a wide range of image representation formats.

Subjective assessment of H.264/AVC video sequences transmitted over a noisy channel

In this paper we describe a database containing subjective assessment scores relative to 78 video streams encoded with H.264/AVC and corrupted by simulating the transmission over error-prone network. The data has been collected from 40 subjects at the premises of two academic institutions. Our goal is to provide a balanced and comprehensive database to enable reproducible research results in the field of video quality assessment. In order to support research works on Full-Reference, Reduced-Reference and No-Reference video quality assessment algorithms, both the uncompressed files and the H.264/AVC bitstreams of each video sequence have been made publicly available for the research community, together with the subjective results of the performed evaluations.

Smart Video Surveillance System Ensuring Privacy

In this paper, we present a smart video surveillance system based on standard technologies and wired or wireless IP networking. The key novelty of the system is that it protects the privacy of people under surveillance. More specifically, a video analysis module detects regions of interest in the scene by change detection or face detection techniques. It is assumed that these regions contain private and sensitive information. Scrambling is then applied only to the corresponding regions. Furthermore, the amount of distortion can be controlled by restricting scrambling to some resolution levels. As a result, the scene remains visible, but privacy-sensitive information is unidentifiable. The scrambling is controlled by a private encryption key which is kept under control of legal authorities. The latter are therefore the only ones who can grant authorization to unlock the protection and view the whole scene. Therefore, this system successfully addresses the loss of privacy issue associated with video surveillance.

Spatio-temporal segmentation based on motion and static segmentation

The problem of segmenting an image sequence in terms of regions characterized by a coherent motion is among the most challenging in image sequence analysis. This paper proposes a new technique which sequentially refines the segmentation and the motion estimation by combining static segmentation and motion information. The motion is robustly computed by a global estimation which remove the camera motion, followed by a local estimation using a matching technique and a robust estimator. Simulation results show the efficiency of the proposed technique.