André Nicoulin

Image Sequence Coding Using Motion Compensated Subband Decomposition

Over the last two decades, the well known Descartes’ phrase “I think therefore I am” became “I communicate therefore I am”. The importance of communication is recognized at all levels, political, social, economical, even if sometimes one forgets to think. Audiovisual signals are the physical support of the information vital for communication.

Motion estimation relaxing the constancy brightness constraint

In the field of motion estimation, the constancy luminance principle has always been used as hypothesis to constrain the problem of optical flow extraction. When real conditions do not satisfy this assumption, classical motion estimation techniques fail. On the basis of models of image representation and image acquisition, a general model that considers brightness changes by means of a multiplicative function and an additive function, has been proposed. In this paper we discuss the problems that such a model poses for the extraction of the optical flow. We show that, in some conditions, the parameters of the model can alias the motion parameters. One consequence is that reliable estimates of the parameters have to be obtained by avoiding aliasing conditions. Another consequence is that some classical techniques, which use multiresolution approaches to solve the problem of local minima for motion estimation, cannot be used anymore. Finally an algorithm that estimates separately brightness change parameters and motion parameters avoiding aliased conditions is presented with simulation results.<<ETX>>

Subband image coding using jointly localized filter banks and entropy coding based on vector quantization

A method for image compression based on subband decomposition is presented. We describe a new filter bank design method for image coding applications and a new entropy coding algorithm for the compression of subband images. A set of relevant optimization criteria is defined for the filter bank design. For the compression, a composite source model is defined by combining vector quantization (VQ) and scalar quantization (SQ) with entropy coding. In the proposed scheme, VQ exploits the remaining statistical dependencies among the subband samples, while SQ allows an optimal control on local distortions. The system is based on a statistical model that uses VQ information to generate low entropy probability tables for an arithmetic coder. The bit rate can be shared between the VQ rate and the SQ rate, allowing many possible configurations in terms of performance and implementation complexity. The proposed system shows improved performance when compared with other existing methods.

Design of parallel multiresolution filter banks by simulated annealing

A new simulated annealing technique is described for designing multiresolution, parallel- structured filter banks with finite wordlength coefficients. The algorithm is based on a two stage optimization. In the first stage, a perturbation following uniform distribution is used; while in the second stage, perturbation is in Gaussian distribution, allowing a faster convergence. The filter banks have properties which make them well suited to image subband coding applications. In particular, they provide joint localization in the spatial and spectral domains, and allow no leakage of DC into higher subbands. This paper describes the algorithm and presents design examples.

Overlapped motion compensation for subband coding of video sequences

Keywords: LTS1 ; LTS3 Reference LTS-ARTICLE-1996-008 Record created on 2006-06-14, modified on 2016-08-08

Overlapped Motion Compensation in Hybrid Video Coding Systems

Keywords: LTS1 ; LTS3 Reference LTS-CONF-1993-004 Record created on 2006-06-14, modified on 2016-08-08

Design of Perfect Reconstruction, Finite Word Length, Nonuniform, and Parallel-structured Filter Banks

Keywords: LTS1 Reference LTS-ARTICLE-1992-002 Record created on 2006-06-14, modified on 2016-08-08

Subband coding of video using energy-adaptive arithmetic coding and statistical feedback-free rate control

An improved video subband coding technique is presented. It is based on a spatially and spectrally localizing subband analysis, followed by scalar quantization and direct arithmetic coding. The quantization and coding parameters are adapted on the basis of local energy of the subband pixels. The proposed technique automatically achieves near-optimal rate allocation with respect to mean-square error (or alternatively, weighted mean-square error). In addition, because arithmetic coding requires no alphabet extension, the quantized subband pixels can be encoded in an arbitrary order without affecting bit rate. This makes it possible to obtain a good statistical estimate of the quantization resolution required to achieve a certain overall bit rate, based on a relatively small random sample of the subband pixels and their corresponding energies. The proposed technique requires that estimates of the local energy of the subband pixels be encoded and sent to the receiver as side-information. A means of accomplishing this, using vector quantization (VQ), is mentioned.

Composite source modeling based on VQ and arithmetic coding for digital subband video compression

We describe a new source model for entropy coding of subband images. It considers and exploits the nonstationary character and the statistical dependencies present in such data in order to achieve higher compression compared to classical methods based on zero order modeling of the subbands. Indeed, images are made up of various regions with different local power spectra, or textures, separated by edges. Therefore, after subband decomposition, the complex and variable statistical dependencies across the subbands at a particular spatial location should be exploited by a proper modeling in order to achieve lower bit costs. A composite source model is proposed for this purpose. It is based on the combination of vector quantization and entropy-coded scalar quantization. An application to digital video compression is also described. Simulation results show a gain of the composite source model in term of bit rate of around 15% to 20% compared to the classical runlength/Huffman coding of the subband samples.<<ETX>>

Statistic model for coding subband images using VQ and arithmetic coding

A new entropy coding algorithm for the compression of subband images is presented. By combining vector quantization (VQ) and scalar quantization (SQ) with entropy coding, the proposed scheme exploits the remaining statistical dependencies among the subband samples, and keeps an optimal control on local distortion by scalar quantization. The system is based on a statistical model which uses VQ information to generate low entropy probability tables for an arithmetic coder. The bit rate can be shared between VQ-rate and SQ-rate, allowing many possible configurations in terms of performances and implementation complexity. The proposed system shows improved performances when compared with other existing methods.