Institute for Systems Research
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Item A Practical Transmission System Based on the Human Visual Model for Satellite Channels(1999) Gu, Junfeng; Jiang, Yimin; Baras, John S.; Baras, John S.; ISR; CSHCNThis paper presents a practical architecture for joint source-channel coding of human visual model-based video transmission over a satellite channel. Perceptual distortion model just-noticeable-distortion (JND) is applied to improve the subjective quality of compressed videos. 3-D wavelet decomposition can remove spatial and temporal redundancy and provide the scalability of video quality.In order to conceal errors occurring under bad channel conditions, a novel slicing method and a joint source channel coding scenario that combines RCPC with CRC and utilizes the distortion information to allocate convolutional coding rates are proposed. A new performance index based on JND is proposed and used to evaluate the overall performance at different signal-to-noise ratios (SNR). Our system uses OQPSK modulation scheme.
The research and scientific content in this material has been submitted to Globecom'99. Item Scalable Coding of Video Objects(1998) Haridasan, Radhakrishan; Baras, John S.; Baras, John S.; ISR; CSHCNThis paper provides a methodology to encode video objects in a scalable manner with regard to both content and quality. Content scalability and quality scalability have been identified as required features in order to support video coding across different environments. Following the object-based approach to coding video, we extend our previous work on motion-based segmentation by using a time recursive approach to segmenting image sequences and decomposing a video "shot" into its constituent objects. Our formulation of the segmentation problem enables us to design a codec in which the information (shape, texture and motion) pertaining to each video object is encoded independently of the other. The multiresolution wavelet decomposition used in encoding texture information is shown to be helpful in providing spatial scalability. Our codec design is also shown to be temporally scalable. This report was accepted for oral presentation at the IEEE International Symposium on Circuits & Systems, Monterey, Calif., May-June 1998.Item Existence and Construction of Optimal Wavelet Basis for Signal Representation(1994) Zhuang, Y.; Baras, John S.; ISR; CSHCNWe study the problem of choosing the optimal wavelet basis with compact support for signal representation and provide a general algorithm for computing the optimal wavelet basis. We first briefly review the multiresolution property of wavelet decomposition and the conditions for generating a basis of compactly supported discrete wavelets in terms of properties of quadrature mirror filter (QMF) banks. We then parametrize the mother wavelet and scaling function through a set of real coefficients. We further introduce the concept of decomposition entropy as an information measure to describe the distance between the given signal and its projection onto the subspace spanned by the wavelet basis in which the signal is to be reconstructed. The optimal basis for a given signal is obtained through minimizing this information measure. We have obtained explicitly the sensitivity of dilations and shifts of the mother wavelet with respect to the coefficient set. A systematic approach is developed in this paper to derive the information gradient with respect to the parameter set from a given square integrable signal and a discrete basis of wavelets. The existence of the optimal basis for the wavelets has been proven in this paper. a gradient based optimization algorithm is developed for computing the optimal wavelet basis.Item Optimal Wavelet Basis Selection for Signal Representation(1994) Zhuang, Y.; Baras, John S.; ISR; CSHCNWe study the problem of choosing the optimal wavelet basis with compact support for signal representation and provide a general algorithm for computing the optimal wavelet basis. We first briefly review the multiresolution property of wavelet decomposition and the conditions for generating a basis of compactly supported discrete wavelets in terms of properties of quadrature mirror filter (QMF) banks. We then parametrize the mother wavelet and scaling function through a set of real coefficients. We further introduce the concept of information measure as a distance measure between the signal and its projection onto the subspace spanned by the wavelet basis in which the signal is to be reconstructed. The optimal basis for a given signal is obtained through minimizing this information measure. We have obtained explicitly the sensitivity of dilations and shifts of the mother wavelet with respect to the coefficient set. A systematic approach is developed here to derive the information gradient with respect to the parameter set for a given square integrable signal and the optimal wavelet basis. A gradient based optimazation algorithm is developed in this paper for computing the optimal wavelet basis.Item Further Results on MAP Optimality and Strong Consistency of Certain Classes of Morphological Filters(1994) Sidiropoulos, N.D.; Baras, John S.; Berenstein, Carlos A.; ISRIn two recent papers [1], [2], Sidiropoulos et al. have obtained statistical proofs of Maximum A Posteriori} (MAP) optimality and strong consistency of certain popular classes of Morphological filters, namely, Morphological Openings, Closings, unions of Openings, and intersections of Closings, under i.i.d. (both pixel-wise, and sequence-wide) assumptions on the noise model. In this paper we revisit this classic filtering problem, and prove MAP optimality and strong consistency under a different, and, in a sense, more appealing set of assumptions, which allows the explicit incorporation of geometric and Morphological constraints into the noise model, i.e., the noise may now exhibit structure; Surprisingly, it turns out that this affects neither the optimality nor the consistency of these field-proven filters.Item Time-Recursive Computation, Part II: Methodology, and Application on QMF Banks and ELT(1993) Frantzeskakis, Emmanuel N.; Baras, John S.; Liu, K.J. Ray; ISRRecent advances in ISDN have promoted applications such as video- phone, tele-conferencing and HDTV, that demand real-time processing of large volume audio, video and speech data. Being the only refuge for this intense computation, the VLSI technology favors modular and regular designs with local communication requirements. In this light, the framework for time-recursive computation, presented in part I [7] of this two-part paper, provides the background for designing efficient VLSI implementations, capable of accommodating high throughput requirements. In part II, we develop a routine that can be used for designing the time-recursive architecture of a given linear operator in a systematic manner. Three classes of QMF banks are used as design examples: the lossless QMF bank, the cosine modulated QMF bank and two Extended Lapped Transforms, one of them being the Modulated Lapped Transform (MLT). In addition to demonstrating the use of the design procedure, these examples provide novel results, interesting on their own right. In particular, the time-recursive architecture we propose for an N - point MLT, also known as Modified DCT or Time Domain Aliasing Cancellation (TDAC) transform, requires 2N + 3 multipliers, 3N + 3 adders and N - 1 rotation circuits.Item Time-Recursive Computation and Real-Time Parallel Architectures, Part I: Framework(1993) Frantzeskakis, Emmanuel N.; Baras, John S.; Liu, K.J. Ray; ISRThe time-recursive computation has been proved as a particularly useful tool in real-time data compression, in transform domain adaptive filtering and in spectrum analysis. Unlike the FFT based ones, the time-recursive architectures require only local communication. Also, they are modular and regular, thus they are very appropriate for VLSI implementation and they allow high degree of parallelism. In this two part paper, we establish an architectural frame work for parallel time-recursive computation. In part I, we consider a class of linear operators that consists of the discrete time, time invariant, compactly supported, but otherwise arbitrary kernel functions. We show that the structure of the realization of a given linear operator is dictated by the decomposition of the latter with respect to proper basis functions. An optimal way for carrying out this decomposition is demonstrated. The parametric forms of the basis functions are identified and their properties pertinent to the architecture design are studied. A library of architectural building modules capable of realizing these functions is developed. An analysis of the implementation complexity for the aforementioned modules is conducted. Based on this framework, an architecture design procedure is developed in Part II [12] that can be used for routinely obtaining the time-recursive architecture of a given linear operator.Item Optimal Filtering of Digital Binary Images Corrupted by Union/Intersection(1992) Sidiropoulos, N.D.; Baras, John S.; Berenstein, Carlos A.; ISRWe model digital binary image data as realizations of a bounded discrete random set, a mathematical object which can be directly defined on a finite lattice. We consider the problem of estimating realizations of discrete random sets distorted by a degradation process which can be described by a union/intersection model. First we present an important structural result concerning the probabilistic specification of discrete random sets defined on a finite lattice. Then we formulate the optimal filtering problem for the case of discrete random sets. Two distinct filtering approaches are pursued. For images which feature strong spatial statistical variations we propose a simple family of spatially varying filters, which we call mask filters, and, for each degradation model, derive explicit formulas for the optimal Mask filter. We also consider adaptive mask filters, which can be effective in a more general setting. For images which exhibit a stationary behavior, we consider the class of Morphological filters. First we provide some theoretical justification for the popularity of certain Morphological filtering schemes. In particular, we show that if the signal is smooth, then these schemes are optimal (in the sense of providing the MAP estimate of the signal) under a reasonable worst-case statistical scenario. Then we show that, by using an appropriate (under a given degradation model) expansion of the optimal filter, we can obtain universal characterizations of optimality which do not rely on strong assumptions regarding the spatial interaction of geometrical primitives of the signal and the noise. This approach corresponds to a somewhat counter- intuitive use of fundamental morphological operators; however it is exactly this mode of the use that enables us to arrive at characterizations of optimality in terms of the fundamental functionals of random set theory, namely the generating functionals of the signal and the noise.Item Structure of Divisible Discrete Random Sets and Their Randomized Superpositions(1991) Sidiropoulos, N.; Baras, John S.; Berenstein, Carlos A.; ISRIn this paper, we present an axiomatic formulation of Discrete Random Sets, and extend Choquet's uniqueness result to obtain a recursive procedure for the computation of the underlying event- space probability law, given a consistent Discrete Random Set specification via its generating functional. Based on this extension, we investigate the structure of Discrete Random Set models that enjoy the properties of independent decomposition/superposition, and present a design methodology for deriving models that are guaranteed to be consistent with some underlying event-space probability law. These results pave the way for the construction of various interesting models, and the solution of statistical inference problems for Discrete Random Sets.Item Bayesian Hypothesis Testing for Boolean Random Sets with Radial Convex Primary Grains Using Morphological Skeleton Transforms(1991) Sidiropoulos, N.; Baras, John S.; Berenstein, Carlos A.; ISRWe consider the problem of binary hypothesis testing for planar Boolean random sets with radial convex primary grains. We show that this problem is equivalent to the problem of binary hypothesis testing for Poisson points on a subset of R cube . The log-likelihood ratio for Poisson points can therefore be applied to observation points on this subset of R cube. Several interesting results pertaining to the asymptotic performance of the log-likelihood ratio for Poisson points are known. A major difficulty with this approach is that the test is based on observation points on a subset of R cube, and is not directly given in terms of the observation of a realization of a Boolean random set. An efficient means of mapping realizations of planar Boolean random sets to corresponding realizations of Poisson point processes on this subset of R cube is needed in order to implement the test. We show that this can be achieved via a class of morphological transformations known as morphological skeleton transforms. These transforms are flexible shape-size analysis tools based on elementary morphological and set-theoretic operations. This is the principal contribution of this paper.