Engineering topics

Park, Stephen K.

Publications and source records attributed to Park, Stephen K..

At least 19 records

NASA NTRS2000

Robust Adaptive Data Encoding and Restoration

This is the final report for NASA cooperative agreement and covers the period from 01 October, 1997 to 11 April, 2000. The research during this period was performed in three primary, but related, areas. 1. Evaluation of integrated information adaptive imaging. 2. Improvements in memory utilization and performance of the multiscale retinex with color restoration (MSRCR). 3. Commencement of a theoretical study to evaluate the non-linear retinex image enhancement technique. The research resulted in several publications, and an intellectual property disclosure to the NASA patent council in May, 1999.

Park, Stephen K.↗

NASA NTRS1999

Fidelity Analysis of Sampled Imaging Systems

Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image reconstruction filtering; and the aliased noise component accounts for the frequency folding effect of sampling, modulated by digital processing and image reconstruction filtering.

Park, Stephen K.↗

NASA NTRS1999

Information-Theoretic Assessment of Sample Imaging Systems

By rigorously extending modern communication theory to the assessment of sampled imaging systems, we develop the formulations that are required to optimize the performance of these systems within the critical constraints of image gathering, data transmission, and image display. The goal of this optimization is to produce images with the best possible visual quality for the wide range of statistical properties of the radiance field of natural scenes that one normally encounters. Extensive computational results are presented to assess the performance of sampled imaging systems in terms of information rate, theoretical minimum data rate, and fidelity. Comparisons of this assessment with perceptual and measurable performance demonstrate that (1) the information rate that a sampled imaging system conveys from the captured radiance field to the observer is closely correlated with the fidelity, sharpness and clarity with which the observed images can be restored and (2) the associated theoretical minimum data rate is closely correlated with the lowest data rate with which the acquired signal can be encoded for efficient transmission.

Huck, Friedrich O.↗

NASA NTRS1998

Information-Adaptive Image Encoding and Restoration

The multiscale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. A number of algorithms exist that provide one or more of these features, but not all. In this paper we compare the performance of the MSRCR with techniques that are widely used for image enhancement. Specifically, we compare the MSRCR with color adjustment methods such as gamma correction and gain/offset application, histogram modification techniques such as histogram equalization and manual histogram adjustment, and other more powerful techniques such as homomorphic filtering and 'burning and dodging'. The comparison is carried out by testing the suite of image enhancement methods on a set of diverse images. We find that though some of these techniques work well for some of these images, only the MSRCR performs universally well oil the test set.

Park, Stephen K.↗

NASA NTRS1993

Aliasing as noise - A quantitative and qualitative assessment

We present a model-based argument that, for the purposes of system design and digital image processing, aliasing should be treated as signal-dependent additive noise. By using a computational simulation based on this model, we process (high resolution images of) natural scenes in a way which enables the 'aliased component' of the reconstructed image to be isolated unambiguously. We demonstrate that our model-based argument leads naturally to system design metrics which quantify the extent of aliasing. And, by illustrating several aliased component images, we provide a qualitative assessment of aliasing as noise.

Park, Stephen K.↗

NASA NTRS1992

Model-based frequency response characterization of a digital-image analysis system for epifluorescence microscopy

Consideration is given to a model-based method for estimating the spatial frequency response of a digital-imaging system (e.g., a CCD camera) that is modeled as a linear, shift-invariant image acquisition subsystem that is cascaded with a linear, shift-variant sampling subsystem. The method characterizes the 2D frequency response of the image acquisition subsystem to beyond the Nyquist frequency by accounting explicitly for insufficient sampling and the sample-scene phase. Results for simulated systems and a real CCD-based epifluorescence microscopy system are presented to demonstrate the accuracy of the method.

Hazra, Rajeeb↗

NASA NTRS1992

Estimating the probability of failure when testing reveals no failures

Formulas for estimating the probability of failure when testing reveals no errors are introduced. These formulas incorporate random testing results, information about the input distribution, and prior assumptions about the probability of failure of the software. The formulas are not restricted to equally likely input distributions, and the probability of failure estimate can be adjusted when assumptions about the input distribution change. The formulas are based on a discrete sample space statistical model of software and include Bayesian prior assumptions. Reusable software and software in life-critical applications are particularly appropriate candidates for this type of analysis.

Miller, Keith W.↗

NASA NTRS1992

Small-kernel, constrained least-squares restoration of sampled image data

Following the work of Park (1989), who extended a derivation of the Wiener filter based on the incomplete discrete/discrete model to a more comprehensive end-to-end continuous/discrete/continuous model, it is shown that a derivation of the constrained least-squares (CLS) filter based on the discrete/discrete model can also be extended to this more comprehensive continuous/discrete/continuous model. This results in an improved CLS restoration filter, which can be efficiently implemented as a small-kernel convolution in the spatial domain.

Hazra, Rajeeb↗

NASA NTRS1991

Solution to the indexing problem of frequency domain simulation experiments

A frequency domain simulation experiment is one in which selected system parameters are oscillated sinusoidally to induce oscillations in one or more system statistics of interest. A spectral (Fourier) analysis of these induced oscillations is then performed. To perform this spectral analysis, all oscillation frequencies must be referenced to a common, independent variable - an oscillation index. In a discrete-event simulation, the global simulation clock is the most natural choice for the oscillation index. However, past efforts to reference all frequencies to the simulation clock generally yielded unsatisfactory results. The reason for these unsatisfactory results is explained in this paper and a new methodology which uses the simulation clock as the oscillation index is presented. Techniques for implementing this new methodology are demonstrated by performing a frequency domain simulation experiment for a network of queues.

Mitra, Mousumi↗

NASA NTRS1991

Small convolution kernels for high-fidelity image restoration

An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

Reichenbach, Stephen E.↗

NASA NTRS1990

Spectral Analysis Of Linear, Shift-Invariant Interpolants

Method of analysis provides quantitative measure of reconstruction and interpolation performances of linear, shift-invariant interpolants. Criterion of performance based upon mean-square error of difference between sampled and reconstructed functions. Applicable to reconstruction algorithms used in processing of signals and images and to types of interpolants used in numerical analysis, computer-aided design, and computer graphics.

Lansing, Donald L.↗

NASA NTRS1990

Digital image gathering and minimum mean-square error restoration

Most digital image restoration algorithms are inherently incomplete because they are conditioned on a discrete-input, discrete-output model which only accounts for blurring during image gathering and additive noise. For those restoration applications where sampling and reconstruction are important, the restoration algorithm should be based on a more comprehensive end-to-end model which also accounts for the potentially important noiselike effects of aliasing and the low-pass filtering effects of interpolative reconstruction. It is demonstrated that although the mathematics of this more comprehensive model is more complex, the increase in complexity is not so great as to prevent a complete development and analysis of the associated minimum mean-square error (Wiener) restoration filter.

Park, Stephen K.↗

NASA NTRS1989

Visual Information Processing for Television and Telerobotics

This publication is a compilation of the papers presented at the NASA conference on Visual Information Processing for Television and Telerobotics. The conference was held at the Williamsburg Hilton, Williamsburg, Virginia on May 10 to 12, 1989. The conference was sponsored jointly by NASA Offices of Aeronautics and Space Technology (OAST) and Space Science and Applications (OSSA) and the NASA Langley Research Center. The presentations were grouped into three sessions: Image Gathering, Coding, and Advanced Concepts; Systems; and Technologies. The program was organized to provide a forum in which researchers from industry, universities, and government could be brought together to discuss the state of knowledge in image gathering, coding, and processing methods.

Huck, Friedrich O.↗

NASA NTRS1989

Linear digital imaging system fidelity analysis

The combined effects of imaging gathering, sampling and reconstruction are analyzed in terms of image fidelity. The analysis is based upon a standard end-to-end linear system model which is sufficiently general so that the results apply to most line-scan and sensor-array imaging systems. Shift-variant sampling effects are accounted for with an expected value analysis based upon the use of a fixed deterministic input scene which is randomly shifted (mathematically) relative to the sampling grid. This random sample-scene phase approach has been used successfully by the author and associates in several previous related papers.

Park, Stephen K.↗

NASA NTRS1989

Model-based quantification of image quality

In 1982, Park and Schowengerdt published an end-to-end analysis of a digital imaging system quantifying three principal degradation components: (1) image blur - blurring caused by the acquisition system, (2) aliasing - caused by insufficient sampling, and (3) reconstruction blur - blurring caused by the imperfect interpolative reconstruction. This analysis, which measures degradation as the square of the radiometric error, includes the sample-scene phase as an explicit random parameter and characterizes the image degradation caused by imperfect acquisition and reconstruction together with the effects of undersampling and random sample-scene phases. In a recent paper Mitchell and Netravelli displayed the visual effects of the above mentioned degradations and presented subjective analysis about their relative importance in determining image quality. The primary aim of the research is to use the analysis of Park and Schowengerdt to correlate their mathematical criteria for measuring image degradations with subjective visual criteria. Insight gained from this research can be exploited in the end-to-end design of optical systems, so that system parameters (transfer functions of the acquisition and display systems) can be designed relative to each other, to obtain the best possible results using quantitative measurements.

Hazra, Rajeeb↗

NASA NTRS1989

Optimal focal-plane restoration

Image restoration can be implemented efficiently by calculating the convolution of the digital image and a small kernel during image acquisition. Processing the image in the focal-plane in this way requires less computation than traditional Fourier-transform-based techniques such as the Wiener filter and constrained least-squares filter. Here, the values of the convolution kernel that yield the restoration with minimum expected mean-square error are determined using a frequency analysis of the end-to-end imaging system. This development accounts for constraints on the size and shape of the spatial kernel and all the components of the imaging system. Simulation results indicate the technique is effective and efficient.

Reichenbach, Stephen E.↗

NASA NTRS1988

Digital enhancement of flow field images

Most photographs of experimentally generated fluid flow fields have inherently poor photographic quality, specifically low contrast. Thus, there is a need to establish a process for quickly and accurately enhancing these photographs to provide improved versions for physical interpretation, analysis, and publication. A sequence of digital image processing techniques which have been demonstrated to effectively enhance such photographs is described.

Kudlinski, Robert A.↗

NASA NTRS1988

Image-gathering system design for information and fidelity

Image gathering and processing are assessed in terms of information and fidelity, and the relationship between these two figures of merit is examined. It is assumed that the system is linear and isoplanatic and that the signal and noise amplitudes are Gaussian, wide-sense stationary, and statistically independent. Within these constraints, it is found that the combined process of image gathering and reconstruction (which is intended to reproduce the output of the image-gathering system) behaves as optical, or photographic, image formation in that the informationally optimized design of the image-gathering system ordinarily does not maximize the fidelity of the reconstructed image. The combined process of image gathering and restoration (which is intended to reproduce the input of the image-gathering system) behaves more as a communication channel in that the informationally optimized design of the image-gathering system tends to maximize the fidelity of optimally restored representations of the input.

Huck, Friedrich O.↗