Journal paper abstracts

J. Konrad and E. Dubois, "Bayesian estimation of motion vector fields," IEEE Trans. Pattern Anal. Machine Intell., vol. 14, pp. 910-927, Sept. 1992, [gzip-compressed PS: 253KB], [PDF: 1,403KB].

This paper presents a new approach to the estimation of two-dimensional motion vector fields from time-varying images. The approach is stochastic, both in its formulation and in the solution method. The formulation involves the specification of a deterministic structural model, along with stochastic observation and motion field models. Two motion models are proposed: a globally smooth model based on vector Markov random fields and a piecewise smooth model derived from coupled vector-binary Markov random fields. Two estimation criteria are studied. In the Maximum A Posteriori Probability (MAP) estimation the a posteriori probability of motion given data is maximized, while in the Minimum Expected Cost (MEC) estimation the expectation of a certain cost function is minimized. The MAP estimation is performed via simulated annealing , while the MEC algorithm performs iteration-wise averaging. Both algorithms generate sample fields by means of stochastic relaxation implemented via the Gibbs sampler . Two versions are developed, one for a discrete state space, the other for a continuous state space. The MAP estimation is incorporated into a hierarchical environment to deal efficiently with large displacements. Numerous experimental results of application of these algorithms to natural and computer-generated images with natural and synthetic motion are shown.

Conference paper abstracts

J. Konrad, "Use of colour in gradient-based estimation of dense two-dimensional motion," in Proc. Conf. Vision Interface VI'92, pp. 103-109, May 1992, [gzip-compressed PS: 452KB].

This paper presents a gradient-based approach to the multi-constraint estimation of dense two-dimensional (2-D) motion. The formulation is based on feature-invariance along motion trajectories and applies motion smoothness constraint to reduce ill-posedness. It permits the use of various image features as the input, for example intensity and colours, or sub-bands of a spectral decomposition. The proposed cost function is minimized using a sequence of quadratic approximations of the matching error and solving the resulting linear system by deterministic relaxation. The proposed algorithm is a generalization of the Horn and Schunck algorithm to the case of vector data. Results of application of the proposed technique to the estimation of 2-D motion from TV images are shown. The obtained motion fields are applied to motion-compensated temporal interpolation resulting in significant but localized improvements.

J. Konrad, J. Radecki, and E. Dubois, "On the design of finite wordlength IIR filters for video applications," in Proc. IEEE Int. Conf. Acoustics Speech Signal Processing, vol. 4, pp. 341-344, Mar. 1992, [gzip-compressed PS: 40KB].

This paper addresses the problem of designing finite precision one-dimensional (1-D) infinite impulse response (IIR) digital filters for video processing. The design algorithm is based on simultaneous minimization of magnitude, phase and stability errors in a discrete space of solutions using simulated annealing . It is demonstrated that the approach results in filters characterized by a substantially reduced non-linearity of the phase response in filter pass band, which is critical in any video processing application. To reduce image degradations due to ripples of the filter step response, another error term is introduced into the cost function. It is demonstrated that this additional term permits significant reduction of step response overshoots, and thus the visibility of degradations in a filtered image. The designed IIR filters are compared with their finite impulse response (FIR) counterparts in terms of characteristic parameters as well as distortion visibility in processed images.

J. Radecki, J. Konrad, and E. Dubois, "Design of finite wordlength 2-D IIR filters using simulated annealing," in Signal Process. VI: Theories and Applications (Proc. Sixth European Signal Process. Conf.), pp. 953-956, Aug. 1992, [gzip-compressed PS: 106KB].

This paper proposes a new approach to the design of two-dimensional (2-D) infinite impulse response (IIR) filters with finite precision coefficients. An objective function is proposed which combines magnitude, phase, step response and stability errors. This function being multidimensional and, in general, non-convex is minimized using simulated annealing . Development of this method constitutes the first step in a feasibility study of the application of 2-D IIR filters to the processing of video signals. Initial results on the design of low-pass filters are very encouraging and compare favourably with similar finite impulse response (FIR) designs.

Technical reports' abstracts

J. Konrad, J. Radecki, and E. Dubois, "The design of 2-D IIR finite wordlength filters for enhanced NTSC encoding and decoding," Tech. Rep. 92-16, INRS-Télécommunications, July 1992.