Multiresolution coding techniques for digital television: A review

Multiresolution decompositions for video coding are reviewed. Both nonrecursive and recursive coding schemes are considered. In nonrecursive schemes, it is shown that pyramid structures have certain advantages over subband or wavelet techniques, and a specific spatiotemporal pyramid coding of HDTV is discussed in some detail. It is shown that recursive, DPCM like schemes will incur a slight loss of optimality due to a restricted form of prediction if multiresolution decomposition with compatible decoding is required. Compatibility and transmission issues are also discussed. Multiresolution transmission for digital broadcast TV is introduced. This, when combined with multiresolution source coding, achieves spectrum efficiency, robustness and graceful degradation under channel impairments.Invited PaperWork supported in part by the National Science Foundation under grants ECD-88-11111, MIP-90-14189 and Bell Communications Research.Work supported by the National Science Foundation under grants ECD-88-11111. K.M. Uz is now with David Sarnoff Research Center in Princeton, NJ 08543.     

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.     

Television by the bit

The various types of advanced television (ATV) are defined, and the most advanced type, high-definition TV (HDTV), is discussed. The present status of HDTV development in the US, Japan, and Europe is examined. Signal processing requirements for HDTV are briefly considered, and the benefits of and prospects for all-digital HDTV are explored. Video compression techniques, implementation issues, and the future of HDTV are also discussed     

Adaptive filtering in subbands with critical sampling: analysis,experiments, and application to acoustic echo cancellation

An exact analysis of the critically subsampled two-band modelization scheme is given, and it is demonstrated that adaptive cross-filters between the subbands are necessary for modelization with small output errors. It is shown that perfect reconstruction filter banks can yield exact modelization. These results are extended to the critically subsampled multiband schemes, and important computational savings are seen to be achieved by using good quality filter banks. The problem of adaptive identification in critically subsampled subbands is considered and an appropriate adaptation algorithm is derived. The authors give a detailed analysis of the computational complexity of all the discussed schemes, and experimentally verify the theoretical results that are obtained. The adaptive behavior of the subband schemes that were tested is discussed     

A Discrete Fourier-Cosine Transform Chip

An 8-point Fourier-cosine transform chip designed for a data rate of 100 Mbits/s is described. The top-down design is presented step by step, including algorithm modification for VLSI suitability, architectural choices, testing overhead, internal precision assignments, mask generation, and finally, verification of the layout. A high-level language (C) design tool was developed concurrently with the layout. This tool allows mimicking exactly the different representations of the algorithm: software, mask, and chip. This provides an automatic cross-checking at all design stages. The VLSI environment created by this tool, as well as existing powerful CAD tools, made a fast design-time possible.     

Framing pyramids

Burt and Adelson (1983) introduced the Laplacian pyramid (LP) as a multiresolution representation for images. We study the LP using the frame theory, and this reveals that the usual reconstruction is suboptimal. We show that the LP with orthogonal filters is a tight frame, and thus, the optimal linear reconstruction using the dual frame operator has a simple structure that is symmetric with the forward transform. In more general cases, we propose an efficient filterbank (FB) for the reconstruction of the LP using projection that leads to a proved improvement over the usual method in the presence of noise. Setting up the LP as an oversampled FB, we offer a complete parameterization of all synthesis FBs that provide perfect reconstruction for the LP. Finally, we consider the situation where the LP scheme is iterated and derive the continuous-domain frames associated with the LP.     

The Distributed Karhunen–Loève Transform

The Karhunen-Loeve transform (KLT) is a key element of many signal processing and communication tasks. Many recent applications involve distributed signal processing, where it is not generally possible to apply the KLT to the entire signal; rather, the KLT must be approximated in a distributed fashion. This paper investigates such distributed approaches to the KLT, where several distributed terminals observe disjoint subsets of a random vector. We introduce several versions of the distributed KLT. First, a local KLT is introduced, which is the optimal solution for a given terminal, assuming all else is fixed. This local KLT is different and in general improves upon the marginal KLT which simply ignores other terminals. Both optimal approximation and compression using this local KLT are derived. Two important special cases are studied in detail, namely, the partial observation KLT which has access to a subset of variables, but aims at reconstructing them all, and the conditional KLT which has access to side information at the decoder. We focus on the jointly Gaussian case, with known correlation structure, and on approximation and compression problems. Then, the distributed KLT is addressed by considering local KLTs in turn at the various terminals, leading to an iterative algorithm which is locally convergent, sometimes reaching a global optimum, depending on the overall correlation structure. For compression, it is shown that the classical distributed source coding techniques admit a natural transform coding interpretation, the transform being the distributed KLT. Examples throughout illustrate the performance of the proposed distributed KLT. This distributed transform has potential applications in sensor networks, distributed image databases, hyper-spectral imagery, and data fusion     

Balanced multiwavelets theory and design

This article deals with multiwavelets, which are a generalization of wavelets in the context of time-varying filter banks and with their applications to signal processing and especially compression. By their inherent structure, multiwavelets are fit for processing multichannel signals. This is the main issue in which we are interested. First, we review material on multiwavelets and their links with multifilter banks and, especially, time-varying filter banks. Then, we have a close look at the problems encountered when using multiwavelets in applications, and we propose new solutions for the design of multiwavelets filter banks by introducing the so-called balanced multiwavelets