The basic vector quantization (VQ) technique employed in video coding belongs to the category of predictive vector quantization (PVQ), as it involves quantization of the (motion compensated) frame prediction error. It is well known that the design of PVQ suffers from fundamental difficulties, due to the prediction loop, which have an impact on the convergence and the stability of the design procedure. We propose an approach to PVQ design that enjoys the stability of open-loop design while it ensures ultimate optimization of the closed-loop system. The method is derived for general predictive quantization, and we demonstrate it on video compression at low bit rates, where it provides substantial improvement over standard open and closed loop design techniques. Further, the approach outperforms standard DCT-based video coding.

The asymptotic closed-loop approach to predictive vector quantizer design with application in video coding

A novel hybrid wavelet video coding algorithm termed video significance-linked connected component analysis (VSLCCA) is developed for very low bit-rate applications. In the proposed VSLCCA codec, first, fine-tuned motion estimation based on the H.263 Recommendation is developed to reduce temporal redundancy, and exhaustive overlapped block motion compensation is utilized to ensure coherency in motion compensated error frames. Second, the wavelet transform is applied to each coherent motion compensated error frame to attain global energy compaction. Third, significant fields of wavelet-transformed error frames are organized and represented as significance-linked connected components so that both the within-subband clustering and the cross-scale dependency are exploited. Last, the horizontal and vertical components of motion vectors are encoded separately using adaptive arithmetic coding while significant wavelet coefficients are encoded in bit-plane order by using high order Markov source modeling and adaptive arithmetic coding. Experimental results on eight standard MPEG-4 test sequences show that for intraframe coding, on average the proposed codec exceeds H.263 and ZTE (zero-tree entropy) in peak signal-to-noise ratio by as much as 2.07 and 1.38 dB at 28 kbit/s, respectively. For entire sequence coding, VSLCCA is superior to H.263 and ZTE by 0.35 and 0.71 dB on average, respectively.

Significance-linked connected component analysis for very low bit-rate wavelet video coding

A new wavelet-based video codec is presented, which joins vectors in the same subbands of different frames in a frame group and uses the properties of the human visual system. Perceptual weights are designed and used in the vector selection and quantisation of the wavelet coefficients. Results indicate a significant improvement in frame quality compared to JPEG2000 image sequence coder.

Adaptive joint subband vector quantisation codec for handheld videophone applications

Lattice vector quantization (LVQ) offers substantial reduction in computational load and design complexity due to the lattice regular structure [1]. In this paper, we extended the SPIHT [2] coding algorithm with lattice vector quantization to code hyperspectral images. In the proposed algorithm, multistage lattice vector quantization (MLVQ) is used to exploit correlations between image slices, while offering successive refinement with low coding complexity and computation. Different four-dimensional lattices and significance metrics are considered. Their rate-distortion performance is compared with other 2D and 3D wavelet-based image compression algorithms.

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Multistage Lattice Vector Quantization for Hyperspectral Image Compression

Lattice vector quantization (LVQ) reduces coding complexity and computation due to its regular structure. A new multistage LVQ (MLVQ) using an adaptive subband thresholding technique is presented and applied to image compression. The technique concentrates on reducing the quantization error of the quantized vectors by "blowing out" the residual quantization errors with an LVQ scale factor. The significant coefficients of each subband are identified using an optimum adaptive thresholding scheme for each subband. A variable length coding procedure using Golomb codes is used to compress the codebook index which produces a very efficient and fast technique for entropy coding. Experimental results using the MLVQ are shown to be significantly better than JPEG 2000 and the recent VQ techniques for various test images.

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A new multistage lattice vector quantization with adaptive subband thresholding for image compression

A novel adaptive vector quantization (VQ) based subband coding scheme for very low bit rate coding of video sequences is presented. Overlapped block motion estimation/compensation is employed to exploit interframe redundancy. A two-dimensional (2-D) wavelet transform (WT) is applied to the resulting displaced frame difference (DFD) signal. The WT coefficients are encoded using an adaptive subband vector quantization (ASBVQ) scheme in combination with a dynamic bit allocation strategy based on marginal analysis. Fixed rate coding is provided. Comparative experimental results of the ASBVQ codec with the H.261 and the H.263 video coding standards are given.

S.P. Voukelatos

Papers

Very low bit-rate color video coding using adaptive subband vector quantization with dynamic bit allocation