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Full-Text Articles in Physics
Gradient-Based Edge Detection Using Nonlinear Edge-Enhancing Prefilters, Russell Hardie, Charles Boncelet
Gradient-Based Edge Detection Using Nonlinear Edge-Enhancing Prefilters, Russell Hardie, Charles Boncelet
Russell C. Hardie
This correspondence examines the use of nonlinear edge enhancers as prefilters for edge detectors. The filters are able to convert smooth edges to step edges and suppress noise simultaneously. Thus, false alarms due to noise are minimized and edge gradient estimates tend to be large and localized. This leads to significantly improved edge maps.
Lum Filters: A Class Of Rank-Order-Based Filters For Smoothing And Sharpening, Russell Hardie, Charles Boncelet
Lum Filters: A Class Of Rank-Order-Based Filters For Smoothing And Sharpening, Russell Hardie, Charles Boncelet
Russell C. Hardie
A new class of rank-order-based filters, called lower-upper-middle (LUM) filters, is introduced. The output of these filters is determined by comparing a lower- and an upper-order statistic to the middle sample in the filter window. These filters can be designed for smoothing and sharpening, or outlier rejection. The level of smoothing done by the filter can range from no smoothing to that of the medianfilter. This flexibility allows the LUM filter to be designed to best balance the tradeoffs between noisesmoothing and signal detail preservation. LUM filters for enhancing edge gradients can be designed to be insensitive to low levels …
Application Of The Stochastic Mixing Model To Hyperspectral Resolution Enhancement, Michael Eismann, Russell Hardie
Application Of The Stochastic Mixing Model To Hyperspectral Resolution Enhancement, Michael Eismann, Russell Hardie
Russell C. Hardie
A maximum a posteriori (MAP) estimation method is described for enhancing the spatial resolution of a hyperspectral image using a higher resolution coincident panchromatic image. The approach makes use of a stochastic mixing model (SMM) of the underlying spectral scene content to develop a cost function that simultaneously optimizes the estimated hyperspectral scene relative to the observed hyperspectral and panchromatic imagery, as well as the local statistics of the spectral mixing model. The incorporation of the stochastic mixing model is found to be the key ingredient for reconstructing subpixel spectral information in that it provides the necessary constraints that lead …
Stochastic Spectral Unmixing With Enhanced Endmember Class Separation, Michael Eismann, Russell Hardie
Stochastic Spectral Unmixing With Enhanced Endmember Class Separation, Michael Eismann, Russell Hardie
Russell C. Hardie
Improvements to an algorithm for performing spectral unmixing of hyperspectral imagery based on the stochastic mixing model (SMM) are presented. The SMM provides a method for characterizing both subpixel mixing of the pure image constituents, or endmembers, and statistical variation in the endmember spectra that is due, for example, to sensor noise and natural variability of the pure constituents. Modifications of the iterative, expectation maximization approach to deriving the SMM parameter estimates are proposed, and their effects on unmixing performance are characterized. These modifications specifically concern algorithm initialization, random class assignment, and mixture constraints. The results show that the enhanced …
Hyperspectral Resolution Enhancement Using High-Resolution Multispectral Imagery With Arbitrary Response Functions, Michael Eismann, Russell Hardie
Hyperspectral Resolution Enhancement Using High-Resolution Multispectral Imagery With Arbitrary Response Functions, Michael Eismann, Russell Hardie
Russell C. Hardie
A maximum a posteriori (MAP) estimation method for improving the spatial resolution of a hyperspectral image using a higher resolution auxiliary image is extended to address several practical remote sensing situations. These include cases where: 1) the spectral response of the auxiliary image is unknown and does not match that of the hyperspectral image; 2) the auxiliary image is multispectral; and 3) the spatial point spread function for the hyperspectral sensor is arbitrary and extends beyond the span of the detector elements. The research presented follows a previously reported MAP approach that makes use of a stochastic mixing model (SMM) …
Improved Optimization Of Soft Partition Weighted Sum Filters And Their Application To Image Restoration, Yong Lin, Russell Hardie, Qin Sheng, Kenneth Barner
Improved Optimization Of Soft Partition Weighted Sum Filters And Their Application To Image Restoration, Yong Lin, Russell Hardie, Qin Sheng, Kenneth Barner
Russell C. Hardie
Soft-partition-weighted-sum (Soft-PWS) filters are a class of spatially adaptive moving-window filters for signal and image restoration. Their performance is shown to be promising. However, optimization of the Soft-PWS filters has received only limited attention. Earlier work focused on a stochastic-gradient method that is computationally prohibitive in many applications. We describe a novel radial basis function interpretation of the Soft-PWS filters and present an efficient optimization procedure. We apply the filters to the problem of noise reduction. The experimental results show that the Soft-PWS filter outperforms the standard partition-weighted-sum filter and the Wiener filter.
A Computationally Efficient Super-Resolution Algorithm For Video Processing Using Partition Filters, Balaji Narayanan, Russell Hardie, Kenneth Barner, Min Shao
A Computationally Efficient Super-Resolution Algorithm For Video Processing Using Partition Filters, Balaji Narayanan, Russell Hardie, Kenneth Barner, Min Shao
Russell C. Hardie
We propose a computationally efficient super-resolution (SR) algorithm to produce high-resolution videofrom low-resolution (LR) video using partition-based weighted sum (PWS) filters. First, subpixel motion parameters are estimated from the LR video frames. These are used to position the observed LR pixels into a high-resolution (HR) grid. Finally, PWS filters are employed to simultaneously perform nonuniform interpolation (to fully populate the HR grid) and perform deconvolution of the system point spread function. The PWS filters operate with a moving window. At each window location, the output is formedusing a weighted sum of the present pixels within the window. The weights are …
Super-Resolution For Imagery From Integrated Microgrid Polarimeters, Russell C. Hardie, Daniel A. Lemaster, Bradley Michael Ratliff
Super-Resolution For Imagery From Integrated Microgrid Polarimeters, Russell C. Hardie, Daniel A. Lemaster, Bradley Michael Ratliff
Russell C. Hardie
Imagery from microgrid polarimeters is obtained by using a mosaic of pixel-wise micropolarizers on a focal plane array (FPA). Each distinct polarization image is obtained by subsampling the full FPA image. Thus, the effective pixel pitch for each polarization channel is increased and the sampling frequency is decreased. As a result, aliasing artifacts from such undersampling can corrupt the true polarization content of the scene. Here we present the first multi-channel multi-frame super-resolution (SR) algorithms designed specifically for the problem of image restoration in microgrid polarization imagers. These SR algorithms can be used to address aliasing and other degradations, without …
Joint Wavelet Transform Correlation With Separated Target And Reference Planes, Boon Yi Soon, Mohammad A. Karim, Russell C. Hardie, Mohammad S. Alam
Joint Wavelet Transform Correlation With Separated Target And Reference Planes, Boon Yi Soon, Mohammad A. Karim, Russell C. Hardie, Mohammad S. Alam
Russell C. Hardie
In recent years, we realize the usefulness of feature extraction for optical correlator and hereby, we investigate the capability of Laplace operator in feature extraction of multiple targets. The first-order terms and the false alarm terms in the correlation output would be removed using electronic power spectrum subtraction technique. Most importantly, the entire magneto-optic SLM is completely utilized for displaying only targets in the input scene. A new cost efficient hardware implementation is proposed and aforementioned result of the proposed system is evaluated through computer simulation.