Iole Moccagatta

Motion-compensated generic coding of video based on a multiresolution data structure

We present a generic video codec, which is able to compress image sequences efficiently regardless of their input formats. In addition, this codec supports a wide range of bit rates, without significant changes in its main architecture. A multiresolution representation of the data is generated by a Gabor-like wavelet transform. The motion estimation is performed by a locally adaptive multigrid block-matching technique. This codec can handle both interlaced and progressive input sequences, the temporal redundancies being exploited by interframe/interfield coding. A perceptual quantization of the resulting coefficients is then performed, followed by adaptive entropy coding. Simulations using different test sequences demonstrate a reconstructed signal of good quality for a wide range of bit rates. Thereby demonstrating that this codec can perform generic coding with reduced complexity and high efficiency.

Vector Quantization-Based Motion Field Segmentation under the Entropy Criterion

Abstract This paper proposes a segmentation of block-based motion fields under the constraint of the entropy criterion. The segmentation is performed by a vector quantization technique which associates the segmentation pattern to an element of a codebook. Optimization of the bit rate as a trade-off between motion and segmentation on the one hand and prediction error on the other hand is addressed. An estimation of the amount of information to code the displaced frame difference is derived, making it possible to control the segmentation process. Simulation results show the efficiency of the segmentation method combined with the entropy criterion in a video coding scheme.

A pyramidal vector quantization approach to transform domain

This paper presents an image coding technique which combines pyramidal transform coding and vector quantization (VQ) for the compression of color images. A Gabor-like wavelet transform is performed and a VQ-based scheme is used to code the coefficients. Due to its visual significance, the DC component is PCM coded. In order to take into account the different statistical characteristics and perceptual relevance of the coefficients, a multiresolution and frequency oriented codebook structure is adopted. In order to exploit the residual inter/intra band correlation which exists in the coefficients, a particular vector forming strategy, which follows the pyramidal structure of the data, is introduced. The vectors are composed by coefficients from different frequency ranges inside the same frequency orientation, thus belonging to the same spatial location. Furthermore, the existing correlation between the Y, U and V components motivates the introduction of chrominance subband coefficients in the vectors. Experimental results show good performance at low bitrate.

Lattice vector quantization approach to image coding

In this paper we present an image coding technique which applies a lattice quantizer on the coefficient domain generated by a Gabor-like wavelet transform. The spatial correlation is reduced by this perceptual subband/wavelet transform with efficient implementation. Due to its visual significance, the DC component is PCM coded. The coefficients are then quantized by a block quantizer whose points lie on a lattice, followed by ideal entropy coding. Different truncated lattices have been tested, namely An, Dn, and E8. Simulation results using grayscale images have shown good performance for bit rates lower than 0.5 bits/pixel when the truncated lattice D16 is used.

A digital video codec for medium bitrate transmission

Keywords: LTS1 Reference LTS-CONF-1991-033 Record created on 2006-06-14, modified on 2016-08-08

New trends in image data compression

This paper gives an overview of a number of advanced techniques for image compression, which are under investigation in the Signal Processing Laboratory at the Swiss Federal Institute of Technology of Lausanne. Various applications ranging from High definition television (HDTV) to multimedia will be discussed. In particular, systems based on subband decomposition, edge based representation, as well as symmetries will be presented.

A motion field segmentation to improve moving edges reconstruction in video coding

Block matching motion estimation techniques have shown their efficiency to reduce the temporal redundancy for video coding. However, they tend to introduce annoying block artifacts in the displaced frame difference due to their block-based model. In this paper, we propose a motion field refinement technique in order to overcome these artifacts. The method relies on vector quantization. The patterns to segment the motion field are derived by the LBG algorithm, the training being performed on segmented patterns obtained from natural images. Simulation results show a significant improvement due to the proposed method, in particular moving edges are much better motion compensated and the visual quality is greatly enhanced.<<ETX>>

VLSI implementation for a new video codec

Keywords: LTS1 ; LTS3 Reference LTS-CONF-1992-010 Record created on 2006-10-27, modified on 2016-08-08

An image coding scheme based on perceptually classified VQ for high compression ratios

In this paper we present a coding scheme for color images aiming at high compression ratios. It is based on perceptually classified vector quantization (VQ), where the different classes are chosen to achieve a better quality of the decoded image. Spatial correlation is reduced by a tree structured wavelet decomposition, then prediction of the insignificant coefficients is performed across subbands. Afterwards, the reduced set of data is organized in vectors in such a way that residual intra and inter band correlation are exploited. Finally, such vectors are coded by a classified VQ. Reconstructed images with good quality and a compression ratio higher that 100:1 have been produced by the proposed scheme, which has been shown to outperform the JPEG standard.

Vector quantization (VQ)-based motion field refinement technique for image sequence coding

To reduce temporal redundancies appearing in video sequences block based motion estimation techniques have been successfully applied. However, due to the block-based model blocking artifacts appear in the resulting displaced frame difference reducing the global coding scheme efficiency. In this paper, a motion field refinement technique is proposed to overcome these artifacts. The method is based on segmentation and vector quantization (VQ). The motion field resulting from the block-based motion estimation is segmented using a set of patterns stored in a codebook. These patterns are derived by the LBG algorithm trained on natural edges. The VQ technique allows a low cost data transmission of the segmentation information. Finally, the segmentation is controlled by an entropy criterion, which performs an optimal bit allocation between motion, segmentation, and DFD information. Simulation results show that a significant improvement is achieved using the proposed method. In particular moving edges are much better motion compensated and the visual quality is greatly enhanced.