Andy C. Hung

Portable video-on-demand in wireless communication

Our present ability to work with video has been confined to a wired environment, requiring both the video encoder and decoder to be physically connected to a power supply and a wired communication link. This paper describes an integrated approach to the design of a portable video-on-demand system capable of delivering high-quality image and video data in a wireless communication environment. The discussion will focus on both the algorithm and circuit design techniques developed for implementing a low-power video compression/decompression system at power levels that are two orders of magnitude below existing solutions. This low-power video compression system not only provides a compression efficiency similar to industry standards, but also maintains a high degree of error tolerance to guard against transmission errors often encountered in wireless communication. The required power reduction can best be attained through reformulating compression algorithms for energy conservation. We developed an intra-frame compression algorithm that requires minimal computation energy in its hardware implementations. >

Error resilient pyramid vector quantization for image compression

The robustness of image and video compression in the presence of time-varying channel error has received increased interest with the emergence of portable digital receivers and computers. To achieve robust compression, pyramid vector quantization (PVQ) can be used. It is a fixed-rate quantization scheme suited to Laplacian-like sources, such as those arising from transform and subband image coding. The authors propose a new method of PVQ which not only improves upon the image compression performance of typical JPEG implementations, but also demonstrates excellent resilience to channel error.<<ETX>>

Optimal quantizer step sizes for transform coders

As evidenced by the theoretical modeling and simulation presented, the optimal quantizer solution for run-length and Huffman coding is quite addressable for the Laplacian case. The step sizes may be calculated in advance for images that share common statistics. Furthermore, the model can also be used for other uses such as bit-management for rate control and lower bound estimation for compressed file sizes; it is also the first step in the general solution to the transform coder quantization problem.<<ETX>>

A comparison of fast inverse discrete cosine transform algorithms

The discrete cosine transform (DCT) is often applied to image compression to decorrelate picture data before quantization. This decorrelation results in many of the quantized transform coefficients equaling zero, hence the compression gain. At the decoder, very few nonzero quantized transform coefficients are received, so the input to the inverse DCT is sparse, greatly reducing the required computation. This paper describes different styles of implementations of fast inverse DCTs designed especially for sparse data and compares them on workstation processors.

Error-resilient pyramid vector quantization for image compression

Pyramid vector quantization (PVQ) uses the lattice points of a pyramidal shape in multidimensional space as the quantizer codebook. It is a fixed-rate quantization technique that can be used for the compression of Laplacian-like sources arising from transform and subband image coding, where its performance approaches the optimal entropy-coded scalar quantizer without the necessity of variable length codes. In this paper, we investigate the use of PVQ for compressed image transmission over noisy channels, where the fixed-rate quantization reduces the susceptibility to bit-error corruption. We propose a new method of deriving the indices of the lattice points of the multidimensional pyramid and describe how these techniques can also improve the channel noise immunity of general symmetric lattice quantizers. Our new indexing scheme improves channel robustness by up to 3 dB over previous indexing methods, and can be performed with similar computational cost. The final fixed-rate coding algorithm surpasses the performance of typical Joint Photographic Experts Group (JPEG) implementations and exhibits much greater error resilience.

Low-power signal processing system design for wireless applications

Our ability to work with most multimedia data has been confined to a wired environment, requiring both the data source and the receiver to be physically connected to a power supply and a wired communication link. This article describes the design principles applicable to wireless signal processing systems, using a portable video-on-demand system as an example. The discussion focuses on both the algorithm and circuit design techniques developed for implementing a low-power video compression/decompression system at power levels that are two orders of magnitude below existing solutions. This low-power video compression system not only provides a compression efficiency similar to industry standards, but also maintains a high degree of error tolerance to guard against the transmission errors often encountered in wireless communication.

Statistical Inverse Discrete Cosine Transforms for Image Compression

The Discrete Cosine Transform (DCT) has been applied to image and image sequence compression to decorrelate the picture data before quantization. This decorrelation results in many of the quantized transform coefficients equaling zero, hence the compression gain. For the decoder, the very few, sparsely populated, non-zero transform coefficient can be utilized for great speed-up in the inverse DCT. This paper describes and compares two styles of implementations of fast inverse DCTs for sparse data. The first implementation that we call the symmetric mapped inverse DCT is based on the forward mapped inverse DCT, but our implementation is up to three times faster. The second implementation is based on a scaled inverse DCT, with detection of zero values. Both implementations are tested for speed against other algorithms, under varying degrees of DCT coefficient sparseness.

Video compression for portable communication using pyramid vector quantization of subband coefficients

The authors describes a video compression scheme that performs pyramid vector quantization (PVQ) of subband coefficients and a VLSI architecture for the PVQ decoder. This algorithm not only provides good compression performance, but also results in a low complexity, low power VLSI implementation. Furthermore, this algorithm demonstrates good error resiliency under severe channel distortion without the use of error correction codes. PVQ also allows encoding and decoding to be computation-based instead of memory-based, as in standard VQ, thus allowing for real-time video coding and eliminating the need for large memories. The algorithm and its performance are described in detail, and the chip architecture of the PVQ decoder is presented.<<ETX>>

Multidimensional rotations for robust quantization of image data

Laplacian and generalized Gaussian data arise in the transform and subband coding of images. This paper describes a method of rotating independent, identically distributed (i.i.d.) Laplacian-like data in multiple dimensions to significantly improve the overload characteristics for quantization. The rotation is motivated by the geometry of the Laplacian probability distribution, and can be achieved with only additions and subtractions using a Walsh-Hadamard transform. Its theoretical and simulated results for scalar, lattice, and polar quantization are presented in this paper, followed by a direct application to image compression. We show that rotating the image data before quantization not only improves compression performance, but also increases robustness to the channel noise and deep fades often encountered in wireless communication.

Asynchronous self-timed circuit synthesis with timing constraints

Incorporating timing information into asynchronous self-timed circuit synthesis can improve circuit performance and simplify circuit hardware. Algorithms are presented that use timing constraints to reduce dependencies of circuit behavior on signal transitions. The resulting asynchronous self-timed circuit is not delay-insensitive in general, but preserves the desirable feature of a hazard-free design under the given timing information.<<ETX>>