Wavelet-based Video Research Articles

A FAST WAVELET-BASED VIDEO CODEC AND ITS APPLICATION IN AN IP VERSION 6-READY SERVERLESS VIDEOCONFERENCING SYSTEM

The purpose of this paper is twofold: On the one hand, we propose a fast wavelet-based video codec which is implemented into a real-time video conferencing tool. The proposed codec uses temporal frame difference coding, a computationally low-complex 5/3 tap wavelet transform, and a fast entropy coding scheme based on Golomb–Rice codes. On the other hand, we present an application of the video conferencing tool in a serverless peer-to-peer IP-based communication framework. For mobile communication we propose a simple, ready-to-use location scheme for video conference users in a global network.

Adaptive joint subband vector quantisation codec for handheld videophone applications

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.

Bottom-up motion compensated prediction in wavelet domain for spatially scalable video coding

A new in-band motion compensation algorithm for wavelet-based video coding is proposed: the bottom-up prediction algorithm (BUP). This algorithm overcomes the periodic shift-invariance of the discrete wavelet transform (DWT) and is formalised into prediction rules using filtering operations. The combination of all prediction rules of the BUP algorithm defines a new transform: the bottom-up overcomplete DWT or BUP ODWT, which is shift-invariant. The envisaged application for the BUP algorithm is spatially scalable wavelet video coding.

Perceptually weighted wavelet-based codec for handheld videophone applications

A wavelet-based video codec that utilises the properties of the human visual system is presented. Perceptual weights are employed in the selection and vector quantisation of the wavelet coefficients. The weights are designed for a specific viewing distance and frame size with application to communication using a handheld videophone device. Results indicate a significant improvement in frame quality.

Wavelet-based video coder via bit allocation

We present a video coder based on a bit allocation (BA) scheme for a coding approach where a wavelet-based video compression scheme is used to encode a group of frames (GOF). The proposed new BA method utilizes a Lagrangian multiplier technique to determine the optimal bit rate for each frame of a given GOF in a rate versus weighted distortion sense. The proposed baseline coder sequentially employs the application of the wavelet transform on each frame in the group. In the wavelet domain, an optimal-vector BA (rate-allocation strategy) is being used to distribute the bit budget among the frames. The manipulated frames in each group are quantized and coded using techniques from still-image compression. We describe and demonstrate the performance of the proposed algorithm in wavelet-based coding approaches. The first one, a combination of wavelet still compression and optimal BA (WCBA), is based on frame differences and exploits well the wavelet compression characteristics which keeps, for a given bit budget, the most important features. It does not utilize motion-compensation interpolation or a 3-D wavelet decomposition. In cases where heavy motion is detected, we extend WCBA into a combination of wavelet still compression, optimal BA, motion compensation with block matching, and error correction (WCBAM), which uses block matching for motion estimation, while the residual error of the compression is reduced by applying error correction in the wavelet domain to reduce temporal redundancies.

Video Segmentation in the Wavelet Compressed Domain

Automatic video indexing is an important feature in the design of a video database. Recently, compressed domain techniques have become popular due to their inherent advantages of efficiency and lower complexity. On the other hand, wavelet transform has emerged as a powerful tool for efficient compression of visual information. A variety of wavelet-based video compression techniques have been reported in the literature. However, there has been little work done in the area of video indexing in the wavelet domain. In this paper, we present video segmentation techniques in a wavelet-based compression framework. These techniques employ wavelet coefficients, their distribution, and the motion vectors estimated by the associated video coder. Simulation results show that the proposed techniques provide a good indexing performance at a low complexity.

An experimental system for distributed classroom education

This paper describes an experimental system for classroom-based tele-education based on IP multicast. It gives an overview of the system and describes how the system is designed to avoid a single central point of failure. The system supports locally controlled video mixing, provides simple floor arbitration without a central controller, and finally implements a new wavelet-based video compression scheme to achieve better video quality for large screen projection. The new network protocols involved are briefly described.

Wavelet-based video indexing and querying

We present several algorithms suitable for analysis of broadcast video. First, we show how wavelet analysis of frames of video can be used to detect transitions between shots in a video stream, thereby dividing the stream into segments. Next we describe how each segment can be inserted into a video database using an indexing scheme that involves a wavelet-based "signature." Finally, we show that during a subsequent broadcast of a similar or identical video clip, the segment can be found in the database by quickly searching for the relevant signature. The method is robust against noise and typical variations in the video stream, even global changes in brightness that can fool histogram-based techniques. In the paper, we compare experimentally our shot transition mechanism to a color histogram Implementation, and also evaluate the effectiveness of our database-searching scheme. Our algorithms are very efficient and run in realtime on a desktop computer. We describe how this technology could be employed to construct a "smart VCR" that was capable of alerting the viewer to the beginning of a specific program or identifying commercials and then muting the volume on the TV.

Multiscale video compression using adaptive finite-state vector quantization

We investigate the use of vector quantizers (VQs) with memory to encode image sequences. A multiscale video coding technique using adaptive finite-state vector quantization (FSVQ) is presented. In this technique, a small codebook (subcodebook) is generated for each input vector from a much larger codebook (supercodebook) by the selection (through a reordering procedure) of a set of appropriate codevectors that is the best representative of the input vector. Therefore, the subcodebook dynamically adapts to the characteristics of the motion-compensated frame difference signal. Several reordering procedures are introduced, and their performance is evaluated. In adaptive FSVQ, two different methods, predefined thresholding and rate-distortion cost optimization, are used to decide between the supercodebook and subcodebook for encoding a given input vector. A cache-based vector quantizer, a form of adaptive FSVQ, is also presented for very-low-bit-rate video coding. An efficient bit-allocation strategy using quadtree decomposition is used with the cache-based VQ to compress the video signal. The proposed video codec outperforms H.263 in terms of the peak signal-to-noise ratio and perceptual quality at very low bit rates, ranging from 5 to 20 kbps. The picture quality of the proposed video codec is a significant improvement over previous codecs, in terms of annoying distortions (blocking artifacts and mosquito noises), and is comparable to that of recently developed wavelet-based video codecs. This similarity in picture quality can be explained by the fact that the proposed video codec uses multiscale segmentation and subsequent variable-rate coding, which are conceptually similar to wavelet-based coding techniques. The simplicity of the encoder and decoder of the proposed codec makes it more suitable than waveletbased coding for real-time, very-low-bit-rate video applications. © 1998 SPIE and IS&T. [S1017-9909(98)00204-9]

Highly scalable wavelet-based video codec for very low bit-rate environment

We introduce a highly scalable video compression system for very low bit-rate videoconferencing and telephony applications around 10-30 kbits/s. The video codec first performs a motion-compensated three-dimensional (3-D) wavelet (packet) decomposition of a group of video frames, and then encodes the important wavelet coefficients using a new data structure called tri-zerotrees (TRI-ZTR). Together, the proposed video coding framework forms an extension of the original zero tree idea of Shapiro (1992) for still image compression. In addition, we also incorporate a high degree of video scalability into the codec by combining the layered/progressive coding strategy with the concept of embedded resolution block coding. With scalable algorithms, only one original compressed video bit stream is generated. Different subsets of the bit stream can then be selected at the decoder to support a multitude of display specifications such as bit rate, quality level, spatial resolution, frame rate, decoding hardware complexity, and end-to-end coding delay. The proposed video codec also allows precise bit rate control at both the encoder and decoder, and this can be achieved independently of the other video scaling parameters. Such a scheme is very useful for both constant and variable bit rate transmission over mobile communication channels, as well as video distribution over heterogeneous multicast networks. Finally, our simulations demonstrated comparable objective and subjective performance when compared to the ITU-T H.263 video coding standard, while providing both multirate and multiresolution video scalability.

A DSP for DCT-based and wavelet-based video codecs for consumer applications

We have developed a video digital signal processor (VDSP1) which performs real-time encoding and decoding for discrete cosine transform- (DCT-) based algorithms such as ITU-T H.261, H.263 and wavelet-based subband encoding algorithms. This LSI is suitable for consumer applications, as it was implemented using 0.5 /spl mu/m CMOS process technology to realize compactness (one million transistors on 65 mm/sup 2/) and low power (maximum: 560 mW). It features a processing unit which performs wavelet filtering at high speeds, a compact DCT circuit, and a fast, flexible DRAM interface for low-cost systems. At 40 MHz, a single chip is capable of processing quarter common intermediate format (QCIF) (176/spl times/144 pixels) size pictures at a rate greater than 15 frames/s.

A cellular neural network for clustering-based adaptive quantization in subband video compression

This paper presents a novel cellular connectionist model for the implementation of a clustering-based adaptive quantization in video coding applications. The adaptive quantization has been designed for a wavelet-based video coding system with a desired scene adaptive and signal adaptive quantization. Since the adaptive quantization is accomplished through a maximum a posteriori probability (MAP) estimation-based clustering process, its massive computation of neighborhood constraints makes it difficult for a software-based real-time implementation of video coding applications. The proposed cellular connectionist model aims at designing an architecture for the real-time implementation of the clustering-based adaptive quantization. With a cellular neural network architecture mapping onto the image domain, the powerful Gibbs spatial constraints are realized through interactions among neurons connected with their neighbors. In addition, the computation of coefficient distribution is designed as an external input to each component of a neuron or processing element (PE). We prove that the proposed cellular neural network does converge to the desired steady state with the proposed, update scheme. This model also provides a general architecture for image processing tasks with Gibbs spatial constraint-based computations.

Face location in wavelet-based video compression for high perceptual quality videoconferencing

We present a human face location technique based on contour extraction within the framework of a wavelet-based video compression scheme for videoconferencing applications. In addition to an adaptive quantization in which spatial constraints are enforced to preserve perceptually important information at low bit rates, semantic information of the human face is incorporated to design a hybrid compression scheme for videoconferencing since the human face is often the most important portion within a frame and should be coded with high fidelity. The human face is detected based on contour extraction and feature point analysis. An approximated face mask is then used in the quantization of the decomposed subbands. At the same total bit rate, coarser quantization of the background enables the face region to be quantized finer and coded with higher quality. Simulation results have shown that the perceptual image quality can be greatly improved using the proposed scheme.