Prof. Stephen E. Reichenbach Profile

Prof. Stephen E. Reichenbach

Professor at Univ of Nebraska Lincoln

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Publications (28)

Proceedings Article | 28 April 2009 Paper

Visualization and analysis of large three-dimensional hyperspectral images

Stephen Reichenbach, Xue Tian, Robert Lindquist, Qingping Tao, Alex Henderson, John Vickerman

Proceedings Volume 7341, 734108 (2009) https://doi.org/10.1117/12.820870

KEYWORDS: Visualization, Ions, Visual analytics, 3D image processing, Toxic industrial chemicals, Hyperspectral imaging, Biological research, Chemical analysis, Analytical research, Mass spectrometry

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SPIE Journal Paper | 1 July 2007

Gradient-based value mapping for pseudocolor images

Arvind Visvanathan, Stephen Reichenbach, Qingping Tao

JEI, Vol. 16, Issue 03, 033004, (July 2007) https://doi.org/10.1117/12.10.1117/1.2778426

KEYWORDS: Visualization, Associative arrays, Chromatography, Chemical analysis, RGB color model, Sensors, Modulation, Computer science, Computer engineering, Visual information processing

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Proceedings Article | 12 May 2006 Paper

Gradient-based value mapping for colorization of two-dimensional fields

Arvind Visvanathan, Stephen Reichenbach, Qingping Tao

Proceedings Volume 6246, 62460I (2006) https://doi.org/10.1117/12.669839

KEYWORDS: Visualization, Associative arrays, Image visualization, Chromatography, Chemical analysis, Sensors, RGB color model, Digital image processing, Digital imaging, Modulation

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Proceedings Article | 25 May 2005 Paper

Cubic convolution for super-resolution from microscanned images

Jiazheng Shi, Stephen Reichenbach, James Howe

Proceedings Volume 5817, (2005) https://doi.org/10.1117/12.606625

KEYWORDS: Super resolution, Imaging systems, Convolution, Image processing, Filtering (signal processing), Systems modeling, Point spread functions, Image resolution, Image registration, Image filtering

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Proceedings Article | 21 September 2004 Paper

Using edge pattern matching for automatic chemical identification in GCXGC

Mingtian Ni, Stephen Reichenbach

Proceedings Volume 5426, (2004) https://doi.org/10.1117/12.543064

KEYWORDS: Chemical analysis, Image processing, Chemical reactions, Detection and tracking algorithms, Liquid crystals, Chromatography, Data acquisition, Nickel, Affine motion model

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Proceedings Article | 15 July 2004 Paper

Pattern matching by scan-converting polygons

Mingtian Ni, Stephen Reichenbach

Proceedings Volume 5438, (2004) https://doi.org/10.1117/12.543057

KEYWORDS: Detection and tracking algorithms, Distance measurement, Pattern recognition, Liquid crystals, Nickel, Visualization, Algorithm development, Computer science, Computer engineering, Object recognition

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Proceedings Article | 15 August 2003 Paper

Chemical warfare agent detection in complex environments with comprehensive two-dimensional gas chromatography

Stephen Reichenbach, Mingtian Ni, Visweswara Kottapalli, Arvind Visvanathan, Edward Ledford, John Oostdijk, Henk Trap

Proceedings Volume 5085, (2003) https://doi.org/10.1117/12.497346

KEYWORDS: Chemical analysis, Chromatography, Nerve agents, Image processing, Calibration, Environmental sensing, Visualization, Image visualization, Data processing

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Proceedings Article | 8 August 2003 Paper

Interpolation by two-dimensional cubic convolution

Jiazheng Shi, Stephen Reichenbach

Proceedings Volume 5108, (2003) https://doi.org/10.1117/12.497405

KEYWORDS: Convolution, Filtering (signal processing), Image restoration, Image processing, Performance modeling, Digital image processing, Yield improvement, Infrared imaging, Infrared radiation, Fourier transforms

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Proceedings Article | 30 July 2002 Paper

Hyperspectral information efficiency and pattern classification

Stephen Reichenbach, Ram Narayanan

Proceedings Volume 4736, (2002) https://doi.org/10.1117/12.477568

KEYWORDS: Image classification, Hyperspectral imaging, Classification systems, Signal attenuation, Imaging systems, Systems modeling, Signal to noise ratio, Hyperspectral systems, Interference (communication), Signal processing

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SPIE Journal Paper | 1 July 2002

Information efficiency in hyperspectral imaging systems

Stephen Reichenbach, Luyin Cao, Ram Narayanan

JEI, Vol. 11, Issue 03, (July 2002) https://doi.org/10.1117/12.10.1117/1.1482097

KEYWORDS: Imaging systems, Hyperspectral imaging, Signal to noise ratio, Interference (communication), Mathematical modeling, Fourier transforms, Satellites, Statistical analysis, Image acquisition, Integration

Proceedings Article | 28 August 2001 Paper

Information theoretic assessment and design of hyperspectral imaging systems with nonuniform bandwidths

Luyin Cao, Stephen Reichenbach, Ram Narayanan

Proceedings Volume 4388, (2001) https://doi.org/10.1117/12.438243

KEYWORDS: Hyperspectral imaging, Imaging systems, Signal to noise ratio, Systems modeling, Error analysis, Computing systems, Hyperspectral systems, Statistical analysis, Hyperspectral simulation, Solid state physics

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Proceedings Article | 28 December 2000 Paper

Noise reduction in remote sensing imagery using data masking and principal component analysis

Brian Corner, Ram Narayanan, Stephen Reichenbach

Proceedings Volume 4115, (2000) https://doi.org/10.1117/12.411533

KEYWORDS: Principal component analysis, Image filtering, Denoising, Remote sensing, Image processing, Interference (communication), Image analysis, Error analysis, Landsat, Earth observing sensors

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Proceedings Article | 18 October 1999 Paper

Effect of gray-scale resolution on information content of remote sensing imagery

Ram Narayanan, Thiruchendur Sankaravadivelu, Stephen Reichenbach

Proceedings Volume 3808, (1999) https://doi.org/10.1117/12.365823

KEYWORDS: Image resolution, Remote sensing, Image processing, Backscatter, Sensors, Image filtering, Image classification, Mathematical modeling, Image enhancement, Data modeling

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Proceedings Article | 18 October 1999 Paper

Digital image processing for a new type of chemical separation system

Qiang Song, Ameet Savant, Stephen Reichenbach, Edward Ledford

Proceedings Volume 3808, (1999) https://doi.org/10.1117/12.365811

KEYWORDS: Digital image processing, Chromatography, Capillaries, Image processing, Chemical compounds, Detection and tracking algorithms, Image registration, Visualization, Chemical species, Feature extraction

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Proceedings Article | 18 October 1999 Paper

Principal component analysis of remote sensing imagery: effects of additive and multiplicative noise

Brian Corner, Ram Narayanan, Stephen Reichenbach

Proceedings Volume 3808, (1999) https://doi.org/10.1117/12.365833

KEYWORDS: Principal component analysis, Remote sensing, Image processing, Interference (communication), Radar, Landsat, Synthetic aperture radar, Speckle, Data acquisition, Earth observing sensors

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Proceedings Article | 21 July 1999 Paper

Information theoretic assessment and design of hyperspectral imaging systems

Stephen Reichenbach, Yan Xiong, Ram Narayanan, Luyin Cao

Proceedings Volume 3716, (1999) https://doi.org/10.1117/12.354696

KEYWORDS: Hyperspectral imaging, Imaging systems, Signal to noise ratio, Statistical analysis, Hyperspectral simulation, Hyperspectral systems, Telecommunications, Spectral resolution, Sensors, Convolution

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Proceedings Article | 29 January 1999 Paper

Application of principal component analysis to multisensor classification

Brian Corner, Ram Narayanan, Stephen Reichenbach

Proceedings Volume 3584, (1999) https://doi.org/10.1117/12.339822

KEYWORDS: Principal component analysis, Image classification, Vegetation, Dielectric polarization, Radar, L band, Visualization, Image processing, Data acquisition, RGB color model

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Proceedings Article | 7 January 1999 Paper

Maximum mutual information estimation of a simplified hidden MRF for offline handwritten Chinese character recognition

Yan Xiong, Stephen Reichenbach

Proceedings Volume 3651, (1999) https://doi.org/10.1117/12.335822

KEYWORDS: Data modeling, Statistical modeling, Magnetorheological finishing, Optical character recognition, Data hiding, Pattern recognition, Systems modeling, Statistical analysis, Detection and tracking algorithms, Computer science

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Proceedings Article | 13 November 1996 Paper

Automated cloud cover assessment for Landsat TM images

Ben Hollingsworth, Liqiang Chen, Stephen Reichenbach, Richard Irish

Proceedings Volume 2819, (1996) https://doi.org/10.1117/12.258064

KEYWORDS: Clouds, Visualization, Landsat, Error analysis, Algorithm development, Data centers, Quantization, Image classification, Reflectivity, Earth observing sensors

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Proceedings Article | 20 October 1993 Paper

Constrained least-squares image restoration filters for sampled image data

Rajeeb Hazra, Stephen Park, G. Louis Smith, Stephen Reichenbach

Proceedings Volume 2028, (1993) https://doi.org/10.1117/12.158634

KEYWORDS: Image filtering, Image restoration, Model-based design, Systems modeling, Digital image processing, Imaging systems, Signal to noise ratio, Image acquisition, Linear filtering, Digital imaging

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Proceedings Article | 1 October 1992 Paper

Discrete-cosine transform coding: information and fidelity

Zia-ur Rahman, Rachel Alter-Gartenberg, Stephen Reichenbach

Proceedings Volume 1705, (1992) https://doi.org/10.1117/12.138461

KEYWORDS: Signal to noise ratio, Image processing, Image compression, Quantization, Image restoration, Visualization, Image quality, Visual information processing, Signal processing, Filtering (signal processing)

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Proceedings Article | 1 October 1992 Paper

Efficient high-resolution digital filters for FLIR images

Stephen Reichenbach, Stephen Park, Gary O'Brien, James Howe

Proceedings Volume 1705, (1992) https://doi.org/10.1117/12.138454

KEYWORDS: Image filtering, Imaging systems, Systems modeling, Convolution, Image processing, Optimal filtering, Signal to noise ratio, Digital filtering, Forward looking infrared, Image resolution

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Proceedings Article | 1 November 1991 Paper

Multiresponse imaging system design for improved resolution

Rachel Alter-Gartenberg, Carl Fales, Friedrich Huck, Zia-ur Rahman, Stephen Reichenbach

Proceedings Volume 1605, (1991) https://doi.org/10.1117/12.50223

KEYWORDS: Signal to noise ratio, Image processing, Visual communications, Image resolution, Signal processing, Visualization, Imaging systems, Visual process modeling, Photodetectors, Image visualization

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Proceedings Article | 1 October 1991 Paper

Artificial scenes and simulated imaging

Stephen Reichenbach, Stephen Park, Rachel Alter-Gartenberg, Zia-ur Rahman

Proceedings Volume 1569, (1991) https://doi.org/10.1117/12.48399

KEYWORDS: Image processing, Digital imaging, Imaging systems, Image acquisition, Stochastic processes, Computer simulations, Digital image processing, Signal processing, Point spread functions, Machine vision

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SPIE Journal Paper | 1 February 1991

Characterizing digital image acquisition devices

Stephen Reichenbach, Stephen Park, Ramkumar Narayanswamy

OE, Vol. 30, Issue 02, (February 1991) https://doi.org/10.1117/12.10.1117/12.55783

KEYWORDS: Optical transfer functions, Digital imaging, Signal to noise ratio, Imaging systems, Point spread functions, Super resolution, Cameras, Sensors, Imaging devices, Image acquisition

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Proceedings Article | 1 October 1990 Paper

Information theoretical assessment of digital imaging systems

Sarah John, Zia-ur Rahman, Friedrich Huck, Stephen Reichenbach

Proceedings Volume 1309, (1990) https://doi.org/10.1117/12.21758

KEYWORDS: Image compression, Systems modeling, Image restoration, Image processing, Signal to noise ratio, Visualization, Image quality, Imaging systems, Analytical research, Thermal modeling

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Proceedings Article | 1 September 1990 Paper

Information theoretical assessment of image gathering and coding for digital restoration

Friedrich Huck, Sarah John, Stephen Reichenbach

Proceedings Volume 1360, (1990) https://doi.org/10.1117/12.24173

KEYWORDS: Image compression, Image processing, Signal to noise ratio, Visualization, Image restoration, Image quality, Computer programming, Visual communications, Information visualization, Quantization

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In this paper we are concerned with the end-to-end performance of image gathering, coding, and restoration as a whole rather than as a chain of independent tasks. Our approach evolves from the pivotal relationship that exists between the spectral information density of the transmitted signal and the restorability of images from this signal. The information theoretical assessment accounts for the information density and efficiency of the acquired signal as a function of the image-gathering system design and the radiance-field statistics, and for the information efficiency and data compression that can be gained by combining image gathering with coding to reduce the signal redundancy and irrelevancy. The redundancy reduction is concerned mostly with the statistical properties of the acquired signal, and the irrelevancy reduction is concerned mostly with the visual properties of the scene and the restored image. The results of this assessment lead to intuitively appealing insights about image gathering and coding for digital restoration. Foremost is the realization that images can be restored with better quality and from less data as the information efficiency of the transmitted data is increased, providing that the restoration correctly accounts for the image gathering and coding processes and effectively suppresses the image-display degradations. High information efficiency, in turn, can be attained only by minimizing imagegathering degradations as well as signal redundancy. Another important realization is that the critical constraints imposed on both image gathering and natural vision limit the maximum acquired information density to ~ 4 binary information units (bifs). This information density requires ~ 5-bit encoding for transmission and recording when lateral inhibition is used to compress the dynamic range of the signal (irrelevancy reduction). This number of encoding levels is close (perhaps fortuitously) to the upper limit of the ~ 40 intensity levels that each nerve fiber can transmit, via pulses, from the retina to the visual cortex within ~l/20 sec to avoid prolonging reaction times. If the data are digitally restored as an image on film for ‘best’ visual quality, then the information density may often be reduced to ~3 bifs or even less, depending on the scene, without incurring perceptual degradations because of the practical limitations that are imposed on the restoration. These limitations are not likely to be found in the nervous system of human beings, so that the higher information density of ^4 bifs that the eye can acquire probably contributes effectively to the improvement in visual quality that we always experience when we view a scene directly rather than through the media of image gathering and restoration.

Proceedings Article | 1 September 1990 Paper

Digital image gathering and minimum mean-square error restoration

Stephen Park, Stephen Reichenbach

Proceedings Volume 1360, (1990) https://doi.org/10.1117/12.24172

KEYWORDS: Image restoration, Digital imaging, Image processing, Electronic filtering, Filtering (signal processing), Visual communications, Convolution, Image filtering, Stochastic processes, Visual process modeling

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