Eric Dubois

The goal of this work is to investigate a high quality, low bit rate image sequence coding scheme which takes full advantage of the temporal redundancies. Such schemes will be important for high-compression video coding, such as the one studied in MPEG-4. In conventional image sequence coding, a motion-compensated DPCM configuration is used to remove the temporal redundancies. The performance of the DPCM for such highly correlated sources at rates below one bps degenerates substantially. We have recently shown that for a highly correlated Gauss-Markov source, practical near rate-distortion function performance is possible. We used the entropy-constrained code-excited linear predictive (EC-CELP) quantization scheme to obtain such performances. Hence for low rate image sequence coding, to improve the rate-distortion performance, an EC-CELP configuration can replace the DPCM configuration to quantize the image intensities along motion trajectories. To apply EC-CELP quantization, we first investigate the methods of motion trajectory estimation and propose a temporal block motion compensation configuration. Then, the performance advantage of EC-CELP configuration over the conventional DPCM structures is shown

This paper presents the theory of motion-compensated spatiotemporal filtering of time-varying imagery. The properties of motion trajectories and their relation to displacement fields and velocity fields are presented. The constraints that image motion places on the time-varying image in both the spatiotemporal domain and in the frequency domain are described, along with the implications of these results on motion-compensated filtering and on sampling. An iterative method for estimating motion which generalizes many pixel-oriented and block-oriented methods is presented. Motion-compensated filtering is then applied to the problems of prediction, interpolation, and smoothing.

This paper presents a new formulation of the regularized image up-sampling problem that incorporates models of the image acquisition and display processes. We give a new analytic perspective that justifies the use of total-variation regularization from a signal processing perspective, based on an analysis that specifies the requirements of edge-directed filtering. This approach leads to a new data fidelity term that has been coupled with a total-variation regularizer to yield our objective function. This objective function is minimized using a level-sets motion that is based on the level-set method, with two types of motion that interact simultaneously. A new choice of these motions leads to a stable solution scheme that has a unique minimum. One aspect of the human visual system, perceptual uniformity, is treated in accordance with the linear nature of the data fidelity term. The method was implemented and has been verified to provide improved results, yielding crisp edges without introducing ringing or other artifacts.

We consider the transmission of QCIF resolution (176×144 pixels) video signals over wireless channels at transmission rates of 64 kb/s and below. The bursty nature of the errors on the wireless channel requires careful control of transmission performance without unduly increasing the overhead for error protection. A dual-rate source coder is presented that adaptively selects a coding rate according to the current channel conditions. An automatic repeat request (ARQ) error control technique is employed to retransmit erroneous data-frames. The source coding rate is selected based on the occupancy level of the ARQ transmission buffer. Error detection followed by retransmission results in less overhead than forward error correction for the same quality. Simulation results are provided for the statistics of the frame-error bursts of the proposed system over code division multiple access (CDMA) channels with average bit error rates of 10-3 to 10-4

Stereoscopic visualization systems based on liquid crystal shutter (LCS) eyewear and cathode-ray tube (CRT) displays provide today the best overall quality of three-dimensional (3-D) images and therefore have a dominant position in commercial as well as professional markets. Due to the CRT and LCS characteristics, however, such systems suffer from perceptual crosstalk (“shadows”) at object boundaries that can reduce, and at times inhibit, the ability to perceive depth. In this paper, we propose a method to reduce such crosstalk. We present a simple model for intensity leak, we assess model parameters for a time-sequential LCS/CRT system and we propose a computationally efficient algorithm to eliminate the crosstalk. Since the full crosstalk elimination implies an unacceptable image degradation (reduction of contrast), we study the tradeoff between crosstalk elimination and image contrast. We describe experiments on synthetic and natural stereoscopic images and we discuss informal subjective viewing of processed images. Overall, the viewer response has been very positive; 3-D perception of many objects became either much easier or even effortless. Since the proposed algorithm can be easily implemented in real time (only linear scaling and table look-up are needed), we believe that it can be successfully used today in various stereoscopic applications suffering from image crosstalk. This is particularly true for PC-based 3-D viewing where the algorithm can be executed by the CPU or by an advanced graphics board

A study of block-oriented motion estimation algorithms is presented, and their application to motion-compensated temporal interpolation is described. In the proposed approach, the motion field within each block is described by a function of a few parameters that can represent typical local motion vector fields.. A probabilistic formulation is then used to develop maximum-likelihood (ML) and maximum a posteriori probability