Bonneau, R. J., and Meadows, H. E. A Multiresolution Markov Approach to Model-Based Image Compression, Digital Signal Processing11 (2001) 346 358Currently a large area of research is being devoted to content-based compression due to the JPEG-2000 and MPEG-7 requirements. Recently there has been much work in wavelet and fractal methods for texture and shape segmentation as well as data compression. While these methods do not give optimal least mean square noise performance for a given compression ratio, they contain implicit models for shape and texture coding as a natural part of the compression process. We thus develop an approach for wavelet fractal compression that incorporates these shape and texture models during quantization. Upon decoding, the model regions are preserved for visual or automatic inspection. Our compression models make use of the Mallat Gaussian derivative basis set and an implicit Markov shape and texture structure.
An improved scheme for newspaper block segmentation and classification is described. The newspaper image is first segmented into blocks using three passes of a run-length smoothing algorithm. Blocks may have any shape and need not be non-overlapped rectangles. The height H between the top-line and base-line of lower case letters, and the number of pixels that have values differing from their four neighboring pixels, are measured for simple and reliable block classification. Blocks of different types are compressed based on their own characteristics. Unlike conventional methods, halftone image blocks are treated differently from black and white graphic blocks for better compression. A lossless compression scheme for halftoned images is proposed. Reconstruction of gray-tones from halftone images employing information of both smooth and edgy areas is presented.
Four image reorganization ICs that enable real-time difference encoding for hierarchical lossless image compression are reported. Two image reorganization processors are realized on the focal-plane and two are designed for hybridization to a separate imager IC. The two focal-plane ICs represent the first integration of a 256*256 buried-channel frame-transfer CCD image sensor with additional charge-domain circuitry to enable image reformatting at video rates (28 frames/s). The four ICs generate pyramidal pixel output in 3*3 blocks with the center pixel first. Pixel data reorganization is performed through simultaneous readout of three rows of data, followed by pixel resequencing and sampling to provide differential output. A novel architecture provides simultaneous readout of multiple imager rows on the focal-plane ICs. The ICs have achieved a charge-transfer efficiency (CTE) of 0.99996 in the conventional horizontal and vertical CCD registers, and a CTE of 0.99994 in the SP/sup 3/ registers.< >
Iterated transformation theory (ITT), also known as fractal coding, is a relatively new block compression method which removes redundancies between different scale representations of the uncompressed signal. In ITT coding we are looking for a piecewise continuous mapping from the space of all images with the same support onto itself which has a close approximation of the desired image as a unique fixed point. The mapping is then the code for the image, and for decoding we iterate the mapping on any initial image, orders of magnitude faster than encoding. We have reduced the computational load of finding the piecewise continuous transformation by using a self-organizing feature map (SOFM) artificial neural network which finds similar features in different resolution representations of the image. The patterns are mapped onto a two-dimensional array of formal neurons forming a code book similar to vector quantization (VQ) coding. We use the (SOFM) ordering properties by searching for mapping not only to the best feature match neuron but also to its neighbors in the network. In this paper we describe the ITT-SOFM algorithm and its software implementation with application to image coding of still gray images. Computer simulations show compression results comparable to or better than state-of-the-art VQ coders, and computational complexity better than most of the well known clustering algorithms.
The first integration of a 256*256 buried-channel frame-transfer CCD (charge coupled device) image sensor with CCD-based reformatting circuitry to allow on-chip difference encoding for hierarchical lossless image compression is reported. The 28 frames per second pyramidal pixel output is in 3*3 pixel blocks with the center pixel first. The reformatting circuitry occupies 2% of the active chip area with an estimated power dissipation of 150 mu W at a 30-Hz frame rate.< >
The paper presents the design of a CCD-based codec preprocessor (CP) integrated with an areal imager. 3 x 3 pixel neighborhood blocks, where the center pixel arrives first, are utilized for the lossless compression algorithm in the image coding scheme. A 256 x 256 buried-channel frame transfer device with 15 x 15 square microns pixels is employed as the imager. The neighborhood reconstruction is effected by means of both row regrouping and pixel resequencing operations. Four designs for CCD CP chips are described: two hybridized to the imager array, and two integrated with the imager. The chips operate at a 30 Hz frame rate with power dissipation at less than 10 uW. The size of the hybrid chips is 2.5 x 5.5 sq mm, and the focal-plane chips' CPs require an area of 250 x 400 square microns. The CPs provide differential output appropriate for lossless coding and compression to off-chip electronics when reorganization of the image data into local 3 x 3 neighborhood blocks is complete.
This study revisits simple methods, subsampling and modulo differentiation, to combine them in a system suitable for operation in ISDN as well as non-ISDN environments with good overall performance. The modulo difference of selected pairs of pixels in a digital image enables the design of a hierarchal code which represents the original digital image without any information loss. The pixels are selected by pairing together consecutive non-overlapping pixels in the original image and then in successive subsampled versions of it. The subsampling is 2:1 and, as the pairing, is alternated horizontally and vertically. This algorithm uniquely combines hierarchal and parallel processing. Further processing of the hierarchal code through an entropy coder achieves good compression. If a Huffman code is used, default tables can be designed with minimum penalty. Parallel processing allows the coder to operate at various speeds, up to real time, and the hierarchal data structure enables operations in a progressive transmission mode. The algorithm's inherent simplicity and the use of the modulo difference operation make this coding scheme computationally simple and robust to noise and errors in coding or transmission. The system can be implemented economically in software as well as in hardware. Coder and decoder are symmetrical. Compression results can be slightly improved by using 2-D prediction but at the cost of an increase in system complexity and sensitivity to noise.
Previous article Next article Equivalent Realizations of Linear SystemsL. M. Silverman and H. E. MeadowsL. M. Silverman and H. E. Meadowshttps://doi.org/10.1137/0117037PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] R. E. Kalman, Mathematical description of linear dynamical systems, J. SIAM Control Ser. A, 1 (1963), 152–192 (1963) MR0152167 0145.34301 Google Scholar[2] R. E. Kalman, Canonical structure of linear dynamical systems, Proc. Nat. Acad. Sci. U.S.A., 48 (1962), 596–600 MR0138865 0249.34005 CrossrefISIGoogle Scholar[3] R. E. Kalman, Irreducible realizations and the degree of a rational matrix, J. Soc. Indust. Appl. Math., 13 (1965), 520–544 10.1137/0113034 MR0182479 0161.06704 LinkISIGoogle Scholar[4] Leonard Weiss and , R. E. Kalman, Contributions to linear system theory, Internat. J. Engrg. Sci., 3 (1965), 141–171 10.1016/0020-7225(65)90042-X MR0183559 0136.08702 CrossrefGoogle Scholar[5] D. C. Youla, The synthesis of linear dynamical systems from prescribed weighting patterns, SIAM J. Appl. Math., 14 (1966), 527–549 10.1137/0114047 MR0204180 0145.34603 LinkISIGoogle Scholar[6] C. A. Desoer and , P. P. Varaiya, The minimal realization of a nonanticipative impulse response matrix, Tech. Memo., M-138, Electronics Research Lab., University of California, Berkeley, 1965 Google Scholar[7] L. M. Silverman and , H. E. Meadows, Degrees of controllability in time-variable linear systems, Proc. National Electronics Conference, Vol. 21, 1965, 689–693 Google Scholar[8] L. A. Zadeh and , C. A. Desoer, Linear System Theory, McGraw-Hill, New York, 1963 Google Scholar[9] A. R. Stubberud, A controllability criterion for a class of linear systems, IEEE Trans. Applications and Industry, AI-68 (1964), 411–413 CrossrefGoogle Scholar[10] A. Chang, An algebraic characterization of controllability, IEEE Trans. Automatic Control, AC-10 (1965), 112–113 10.1109/TAC.1965.1098056 CrossrefISIGoogle Scholar[11] L. M. Silverman and , H. E. Meadows, Controllability and time-variable unilateral networks, IEEE Trans. Circuit Theory, CT-12 (1965), 308–314 MR0246709 CrossrefGoogle Scholar[12] L. M. Silverman and , H. E. Meadows, Controllability and observability in time-variable linear systems, SIAM J. Control, 5 (1967), 64–73 10.1137/0305005 MR0209043 0163.11001 LinkGoogle Scholar[13] C. T. Chen, , C. A. Desoer, , A. Niederlinski and , R. E. Kalman, Simplified conditions for controllability and observability of linear time-invariant systems, IEEE Trans. Automatic Control, AC-11 (1966), 613– 10.1109/TAC.1966.1098364 CrossrefISIGoogle Scholar[14] Chi-tsong Chen, Linear independence of analytic functions, SIAM J. Appl. Math., 15 (1967), 1272–1274 10.1137/0115109 MR0224761 0185.29501 LinkISIGoogle Scholar[15] R. E. Kalman, Realization theory for nonconstant linear systems, Unpublished notes Google Scholar[16] R. E. Kalman, On the stability of time-varying linear systems, IRE Trans. Circuit Theory, CT-9 (1962), 420–422 CrossrefGoogle Scholar[17] Leonard H. Haines and , Leonard M. Silverman, Internal and external stability of linear systems, J. Math. Anal. Appl., 21 (1968), 277–286 10.1016/0022-247X(68)90213-8 MR0223669 0155.12903 CrossrefISIGoogle Scholar[18] L. M. Silverman and , B. D. O. Anderson, Controllability, observability and stability of linear systems, SIAM J. Control, 6 (1968), 121–130 10.1137/0306010 MR0233051 0157.15803 LinkISIGoogle Scholar Previous article Next article FiguresRelatedReferencesCited byDetails Appendix: Control and System Theory of Deterministic Systems3 August 2021 Cross Ref State and Loop Equivalence for Linear Parameter Varying Systems16 March 2019 Cross Ref Sliding Mode Tangent Space Observer for LTV Systems with Unknown Inputs Cross Ref Robust State Estimation for Linear Time Varying Lateral Vehicle Dynamics with Unknown Road Curvature Cross Ref State and Loop Equivalence for Linear Parameter Varying Systems Cross Ref Transformations for linear parameter varying systemsIFAC-PapersOnLine, Vol. 51, No. 26 Cross Ref Transition rule of differentially controllable subspace for linear periodic systems Cross Ref Differentially Controllable Subspace for Linear Periodic SystemsIFAC-PapersOnLine, Vol. 49, No. 14 Cross Ref Interpolated Modeling of LPV SystemsIEEE Transactions on Control Systems Technology, Vol. 22, No. 6 Cross Ref Kalman Canonical Decomposition of Linear Time-Varying SystemsIchiro Jikuya and Ichijo Hodaka28 January 2014 | SIAM Journal on Control and Optimization, Vol. 52, No. 1AbstractPDF (393 KB)Theoretical and numerical issues concerning temporal stabilisability and detectabilityIFAC Proceedings Volumes, Vol. 47, No. 1 Cross Ref Temporal and one‐step stabilisability and detectability of discrete‐time linear systems1 January 2013 | IET Control Theory & Applications, Vol. 7, No. 1 Cross Ref Temporal and differential stabilizability and detectability of piecewise constant rank systems13 April 2011 | Optimal Control Applications and Methods, Vol. 33, No. 3 Cross Ref Temporal Linear System StructureIEEE Transactions on Automatic Control, Vol. 53, No. 5 Cross Ref State feedback uniform decoupling problem of linear time-varying analytic systemsJournal of the Franklin Institute, Vol. 330, No. 6 Cross Ref New results in realization theory for linear time-varying analytic systemsIEEE Transactions on Automatic Control, Vol. 24, No. 6 Cross Ref Multivariable System Identification - A SurveyIFAC Proceedings Volumes, Vol. 12, No. 8 Cross Ref Nonstationary network synthesis via state-space techniquesIEEE Transactions on Circuits and Systems, Vol. 22, No. 9 Cross Ref Controllability, Realization and Stability of Discrete-Time SystemsLeonard Weiss18 July 2006 | SIAM Journal on Control, Vol. 10, No. 2AbstractPDF (1937 KB)On Dynamical Systems Realizing Stationary Weighting Patterns and Time-Varying Feedback SystemsR. A. Skoog18 July 2006 | SIAM Journal on Control, Vol. 10, No. 1AbstractPDF (658 KB)Some Results Concerning Time-Varying Networks having a Time-Invariant terminal BehaviorIEEE Transactions on Circuit Theory, Vol. 19, No. 1 Cross Ref Realization of linear dynamical systemsIEEE Transactions on Automatic Control, Vol. 16, No. 6 Cross Ref Synthesis Cross Ref Volume 17, Issue 2| 1969SIAM Journal on Applied Mathematics History Submitted:26 July 1967Published online:12 July 2006 InformationCopyright © 1969 Society for Industrial and Applied MathematicsPDF Download Article & Publication DataArticle DOI:10.1137/0117037Article page range:pp. 393-408ISSN (print):0036-1399ISSN (online):1095-712XPublisher:Society for Industrial and Applied Mathematics
Previous article Next article Controllability and Observability in Time-Variable Linear SystemsL. M. Silverman and H. E. MeadowsL. M. Silverman and H. E. Meadowshttps://doi.org/10.1137/0305005PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] R. E. Kalman, Mathematical description of linear dynamical systems, J. SIAM Control Ser. A, 1 (1963), 152–192 (1963) MR0152167 0145.34301 Google Scholar[2] Leonard Weiss, The concepts of differential controllability and differential observability, J. Math. Anal. Appl., 10 (1965), 442–449 10.1016/0022-247X(65)90139-3 MR0201209 0132.07202 CrossrefISIGoogle Scholar[3] E. Kreindler and , P. E. Sarachik, On the concepts of controllability and observability of linear systems, IEEE Trans. Automatic Control, AC-9 (1964), 129–136 10.1109/TAC.1964.1105665 MR0189852 CrossrefISIGoogle Scholar[4] Earl A. Coddington and , Norman Levinson, Theory of ordinary differential equations, McGraw-Hill Book Company, Inc., New York-Toronto-London, 1955xii+429 MR0069338 0064.33002 Google Scholar[5] L. M. Silverman, Representation and realization of time-variable linear systems, Tech. Rept., 94, Department of Electrical Engineering, Columbia University, New York, 1966 Google Scholar[6] Witold Hurewicz, Lectures on ordinary differential equations, The Technology Press of the Massachusetts Institute of Technology, Cambridge, Mass., 1958xvii+122 MR0090703 0082.29702 CrossrefGoogle Scholar[7] L. M. Silverman and , H. E. Meadows, Controllability and time-variable unilateral networks, IEEE Trans. Circuit Theory, CT-12 (1965), 308–314 MR0246709 CrossrefGoogle Scholar[8] A. R. Stubberud, A controllability criterion for a class of linear systems, IEEE Trans. Applications and Industry, 68 (1964), 411–413 CrossrefGoogle Scholar[9] A. Chang, An algebraic characterization of controllability, IEEE Trans. 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Extensive present demands and much greater projected future needs for high-speed error-free relaying of data have provided an additional stimulus to the communications engineer's interest in efficient transmission and processing of information-bearing signals. A topically well-unified view of current work motivated by this interest was evident in the technical program of the Symposium on Signal Tr...
