Prediction error image coding using a modified stochastic vector quantization scheme

The objective of this paper is to provide an efficient and yet simple method to encode the prediction error image of video sequences, based on a stochastic vector quantization (SVQ) approach that has been modified to cope with the intrinsic decorrelated nature of the prediction error image of video signals. In the SVQ scheme, the codewords are generated by stochastic techniques instead of being generated by a training set representative of the expected input image as is normal use in VQ. The performance of the scheme is shown for the particular case of segmentation-based video coding although the technique can be also applied to motion-compensated hybrid coding schemes.Peer ReviewedPostprint (published version

An Efficient Coding Method for Teleconferencing Video and Confocal Microscopic Image Sequences

In this paper we propose a three-dimensional vector quantization based video coding scheme. The algorithm uses a 3D vector quantization pyramidal code book based model with adaptive code book pyramidal codebook for compression. The pyramidal code book based model helps in getting high compression in case of modest motion. The adaptive vector quantization algorithm is used to train the code book for optimal performance with time. Some of the distinguished features of our algorithm are its excellent performance due to its adaptive behavior to the video composition and excellent compression due to codebook approach. We also propose an efficient codebook based post processing technique which enables the vector quantizer to possess higher correlation preservation property. Based on the special pattern of the codebook imposed by post-processing technique, a window based fast search (WBFS) algorithm is proposed. The WBFS algorithm not only accelerates the vector quantization processing, but also results in better rate-distortion performance. The proposed approach can be used for both teleconferencing videos and to compress images obtained from confocal laser scanning microscopy (CLSM). The results show that the proposed method gave higher subjective and objective image quality of reconstructed images at a better compression ratio and presented more acceptable results when applying image processing filters such as edge detection on reconstructed images. The experimental results demonstrate that the proposed method outperforms the teleconferencing compression standards H.261 and LBG based vector quantization technique

A hybrid low bit-rate video codec using subbands and statistical modeling

A hybrid low bit-rate video codes using subbands and statistical modeling is proposed in this thesis. The redundancy within adjacent video frames is exploited by motion estimation and compensation. The Motion Compensated Frame Difference (MCFD) signals are decomposed into 7 subbands using 2-D dyadic tree structure and separable filters. Some of the subband signals are statistically modeled by using the 2-D AR(1) technique. The model parameters provide a representation of these subbands at the receiver side with a. certain level of error. The remaining subbands are compressed employing a classical waveform coding technique, namely vector quantization (VQ). It is shown that the statistical modeling is a viable representation approach for low-correlated subbands of MCFD signal.The subbands with higher correlation are better represented with waveform coding techniques

Subband Image Coding Using Vector Quantization

Image subband decomposition enables efficient coding matched to the statistics of each subband and human visual characteristics. Vector quantization (VQ) provides a powerful means of bit rate reduction taking advantage of remaining intra and inter band correlation of the decomposed subband images. This paper describes image coding schemes which combines subband decomposition and VQ for still pictures and video sequences. For still picture coding, we propose "same orientation" inter-subband VQ with vector power "thresholding" and "subband limitation". For video sequence coding, we propose subband VQ of motion compensated (MC) prediction difference. Computer simulation results present that 1) "thresholding" and "subband limitation" are very effective for low bit rate coding of still pictures and 2) "same orientation" inter-subband VQ of MC prediction difference shows higher performance than intra-subband VQ for video sequences

Subband Image Coding Using Vector Quantization

Image subband decomposition enables efficient coding matched to the statistics of each subband and human visual characteristics. Vector quantization (VQ) provides a powerful means of bit rate reduction taking advantage of remaining intra and inter band correlation of the decomposed subband images. This paper describes image coding schemes which combines subband decomposition and VQ for still pictures and video sequences. For still picture coding, we propose "same orientation" inter-subband VQ with vector power "thresholding" and "subband limitation". For video sequence coding, we propose subband VQ of motion compensated (MC) prediction difference. Computer simulation results present that 1) "thresholding" and "subband limitation" are very effective for low bit rate coding of still pictures and 2) "same orientation" inter-subband VQ of MC prediction difference shows higher performance than intra-subband VQ for video sequences

Spatiotemporal adaptive quantization for the perceptual video coding of RGB 4:4:4 data

Due to the spectral sensitivity phenomenon of the Human Visual System (HVS), the color channels of raw RGB 4:4:4 sequences contain significant psychovisual redundancies; these redundancies can be perceptually quantized. The default quantization systems in the HEVC standard are known as Uniform Reconstruction Quantization (URQ) and Rate Distortion Optimized Quantization (RDOQ); URQ and RDOQ are not perceptually optimized for the coding of RGB 4:4:4 video data. In this paper, we propose a novel spatiotemporal perceptual quantization technique named SPAQ. With application for RGB 4:4:4 video data, SPAQ exploits HVS spectral sensitivity-related color masking in addition to spatial masking and temporal masking; SPAQ operates at the Coding Block (CB) level and the Prediction Unit (PU) level. The proposed technique perceptually adjusts the Quantization Step Size (QStep) at the CB level if high variance spatial data in G, B and R CBs is detected and also if high motion vector magnitudes in PUs are detected. Compared with anchor 1 (HEVC HM 16.17 RExt), SPAQ considerably reduces bitrates with a maximum reduction of approximately 80%. The Mean Opinion Score (MOS) in the subjective evaluations, in addition to the SSIM scores, show that SPAQ successfully achieves perceptually lossless compression compared with anchors

Wavelet-based video codec using human visual system coefficients for 3G mobiles

A new wavelet based video codec that uses human visual system coefficients is presented. In INTRA mode of operation, wavelet transform is used to split the input frame into a number of subbands. Human Visual system coefficients are designed for handheld videophone devices and used to regulate the quantization stepsize in the pixel quantization of the high frequency subbands’ coefficients. The quantized coefficients are coded using quadtreecoding scheme. In the INTER mode of operation, the displaced frame difference is generated and a wavelet transform decorrelates it into a number of subbands. These subbands are coded using adaptive vector quantization scheme. Results indicate a significant improvement in frame quality compared to motion JPEG200

Intra-WZ quantization mismatch in distributed video coding

During the past decade, Distributed Video Coding (DVC) has emerged as a new video coding paradigm, shifting the complexity from the encoder-to the decoder-side. This paper addresses a problem of current DVC architectures that has not been studied in the literature so far, that is, the mismatch between the intra and Wyner-Ziv (WZ) quantization processes. Due to this mismatch, WZ rate is spent even for spatial regions that are accurately approximated by the side-information. As a solution, this paper proposes side-information generation using selective unidirectional motion compensation from temporally adjacent WZ frames. Experimental results show that the proposed approach yields promising WZ rate gains of up to 7% relative to the conventional method

Mesh-based video coding for low bit-rate communications

In this paper, a new method for low bit-rate content-adaptive mesh-based video coding is proposed. Intra-frame coding of this method employs feature map extraction for node distribution at specific threshold levels to achieve higher density placement of initial nodes for regions that contain high frequency features and conversely sparse placement of initial nodes for smooth regions. Insignificant nodes are largely removed using a subsequent node elimination scheme. The Hilbert scan is then applied before quantization and entropy coding to reduce amount of transmitted information. For moving images, both node position and color parameters of only a subset of nodes may change from frame to frame. It is sufficient to transmit only these changed parameters. The proposed method is well-suited for video coding at very low bit rates, as processing results demonstrate that it provides good subjective and objective image quality at a lower number of required bits