Eric Viscito

The analysis and design of multidimensional FIR perfect reconstruction filter banks for arbitrary sampling lattices

A general analysis of multidimensional multirate filter banks is presented. The approach is applicable to discrete signal spaces of any dimension, to multirate systems based on arbitrary downsampling and upsampling lattices, and for filter banks with any number of channels. A new numerical design procedure is also presented for multidimensional multirate perfect reconstruction filter banks, which is based on methods of nonlinearly constrained numerical optimization. An error function that depends only on the analysis filter impulse response coefficients is minimized, subject to a set of quadratic equality constraints that involve both the analysis and synthesis filter coefficients. With this design framework, it is possible to design a wide variety of filter banks that have a number of desirable properties. The analysis and synthesis filters that result are finite impulse response (FIR) and of equal size. In addition, both paraunitary and nonparaunitary filter banks can be designed with this method. Unlike paraunitary filter banks, nonparaunitary filter banks are capable of performing analysis bank functions more general than band-splitting with flat passband filters. >

Video compression algorithm with adaptive bit allocation and quantization

The emerging ISO MPEG video compression standard is a hybrid algorithm which employs motion compensation, spatial discrete cosine transforms, quantization, and Huffman coding. The MPEG standard specifies the syntax of the compressed data stream and the method of decoding, but leaves considerable latitude in the design of the encoder. Although the algorithm is geared toward fixed-bit-rate storage media, the rules for bit rate control allow a good deal of variation in the number of bits allocated to each picture. In addition, the allocation of bits within a picture is subject to no rules whatsoever. One would like to design an encoder that optimizes visual quality of the decoded video sequence subject to these bit rate restrictions. However, this is difficult due to the elusive nature of a quantitative distortion measure for images and motion sequences that correlates well with human perception. This paper describes an MPEG encoder designed to produce good quality coded sequences for a wide range of video source characteristics and over a range of bit rates. The novel parts of the algorithm include a temporal bit allocation strategy, spatially adaptive quantization, and a bit rate control scheme.

Flexible scalable digital video coding

Abstract In this paper, we describe a video coding algorithm which combines the high visual quality of hybrid motion-compensated transform-based video coding techniques with the functional advantages of scalable, multi-resolution video. The technique produces a hierarchical video data representation by incorporating a simple frequency domain pyramid in a hybrid motion-compensated prediction/discrete cosine transform video coding algorithm. Compared to a single-layer hybrid scheme, this method has a very low penalty in coding efficiency and code complexity.

Motion video adaptive quantization in the transform domain

The authors developed a minimax adaptive quantization algorithm that operates in the discrete cosine transform domain conforming to the Moving Picture Experts Group (MPEG) standard. The algorithm is designed to optimize image quality by adapting a quantizer scaling factor to the local characteristics of the video pictures while preserving a constraint on the average output bit rate. The algorithm is well suited for real-time encoder implementations of current video compression standards, such as MPEG and H.261. >

Runlength encoding of quantized discrete cosine transform (DCT) coefficients

Runlength encoding is used in image and video compression methods to efficiently store quantized Discrete Cosine Transform coefficients. The coefficients for each block are scanned in a zig-zag fashion, and runs of zeros are entropy coded. In this paper we present a comparison of the bit-rate resulting from runlength encoding with the bit-rate calculated as the coefficient-wise sum of entropies. Our experiments with several images show that the two are very close in practice. This is a useful result, for example, for designing quantization matrices to meet any bit-rate requirement. We also present an analytical framework to study these bit- rates. We consider two variants of runlength encoding. In the first one, the symbols that are entropy-coded are (runlength, value) pairs. In the second variant, which is the one used in JPEG, values are grouped together into categories based on magnitude.

Compression algorithms for software coding of video

With the development of high performance desktop computers and workstations, software encoding and decoding of video using a variety of standard and non-standard compression techniques has attracted increased attention recently. New and more powerful processors hold the promise of high speed video encoding and decoding. Diverse applications such as multimedia video retrieval and playback from databases, videotelephony and videoconferencing, video annotation, video electronic mail and video games are examples of promising application areas presently being discussed. A number of commercially available products have already been released. This special issue of Signal Processing: Image Communication addresses aspects of video compression methods relevant to either pure software or for hardware assisted software coding applications. The purpose is to capture the current state of the art of the performance of specific video compression and data representation methods for software implementations and to address problems related to the interaction between the compression methods and hardware platforms. An approach to fast transform coding in software by James D. Allen concentrates on a bottleneck problem for many DCT based image and video compression schemes implemented in software the fast image transform. The author introduces a fast method for computing a linear transform without multiplications, e.g. the DCT or its inverse, on 32-bit processors. Results of the technique for JPEG image compression and decompression in software are provided. Super eficient decoding of color JPEG images on RISC machines by Elliot Linzer presents techniques

Encoding of motion video sequences for the MPEG environment using arithmetic coding

In this paper, we describe a motion-compensated hybrid DCT/DPCM algorithm suitable for compressing motion video sequences at 1-1.5 Mbits/second. The algorithm is compatible with the currently emerging MPEG video compression standard with one exception: the entropy coding of the DCT coefficients, motion vector data and all side information is accomplished via arithmetic coding rather than Huffman coding. The algorithm can be made completely MPEG-compatible with the addition of an arithmetic-Huffman transcoder. Experimental results demonstrate the effect of the proposed changes on the compression efficiency.