Biomedical subjects

Mark A Neifeld

Publications and source records attributed to Mark A Neifeld.

13 recordsLinked to original sources

PubMed2006

Collaborative multihop transmission of distributed sensor imagery.

We consider a network of imaging sensors. We address the problem of energy-efficient communication of the measurements of the sensors. A novel algorithm is presented for the purpose of exploiting intersensor and intrasensor correlation, which is inherent in a network of imaging sensors. The collaborative algorithm is used in conjunction with a cooperative multihop routing strategy to maximize the lifetime of the network. The algorithm is demonstrated to achieve an average gain in the lifetime as high as 3.2 over previous methods.

Algorithms↗

PubMed2006

Feature-specific structured imaging.

We present a feature-specific imaging system based on the use of structured light. Feature measurements are obtained by projecting spatially structured illumination onto an object and collecting all the reflected light onto a single photodetector. Principal component features are used to define the illumination patterns. The optimal linear minimum mean-square error (LMMSE) operator is used to generate object estimates from the measured features. We study the optimal allocation of illumination energy into each feature measurement in the presence of additive white Gaussian detector noise and optical blur. We demonstrate that this new imaging approach reduces imager complexity and provides improved image quality in high noise environments. Compared to the optimal LMMSE postprocessing of a conventional image, feature-specific structured imaging provides a 38% rms error reduction and requires 400 times fewer measurements for a noise standard deviation of sigma = 2 x 10(-3). Experimental results validate these theoretical predictions.

Algorithms↗

PubMed2006

Multiaperture imaging.

We study the reconstruction of a high-resolution image from multiple low-resolution images by using a nonlinear iterative backprojection algorithm. We exploit diversities in the imaging channels, namely, the number of imagers, magnification, position, rotation, and fill factor, to undo the degradation caused by the optical blur, pixel blur, and additive noise. We quantify the improvements gained by these diversities in the reconstruction process and discuss the trade-off among system parameters. As an example, for a system in which the pixel size is matched to the diffraction-limited optical blur size at a moderate detector noise level, we can reduce the reconstruction root-mean-square error by 570% by using 16 cameras and a large amount of diversity. The algorithm was implemented on a 56 camera array specifically constructed to demonstrate the resolution-enhancement capabilities. Practical issues associated with building and operating this device are presented and analyzed.

Journal Article↗

PubMed2006

A method for coordinating the distributed transmission of imagery.

Distributed imaging using sensor arrays is gaining popularity among various research and development communities. A common bottleneck within such an imaging sensor network is the large resulting data load. In applications for which transmission power and/or bandwidth are constrained, this can drastically decrease the sensor network lifetime. We present an algorithm that efficiently exploits inter- and intrasensor correlation for the purpose of power-constrained distributed transmission of sensor-network imagery. Gains in network lifetime up to 114% are obtained when using the suggested algorithm with lossless compression. Our results also demonstrate that when lossy compression is employed, much larger gains are achieved. For example, when a normalized root-mean-squared error of 0.78% can be tolerated in the received measurements, the network lifetime increases by a factor of 2.8, as compared to the (optimized) lossless case.

Algorithms↗

PubMed2006

Reduced-complexity representation of the coherent point-spread function in the presence of aberrations and arbitrarily large defocus.

We introduce a method to analyze the diffraction integral for evaluating the point-spread function. Our method is based on the use of higher-order Airy functions along with Zernike and Taylor expansions. Our approach is applicable when we are considering a finite, arbitrary number of aberrations and arbitrarily large defocus simultaneously. We present an upper bound for the complexity and the convergence rate of this method. We also compare the cost and accuracy of this method with those of traditional ones and show the efficiency of our method through these comparisons. In particular, we rigorously show that this method is constructed in a way that the complexity of the analysis (i.e., the number of terms needed for expressing the light disturbance) does not increase as either defocus or resolution of interest increases. This has applications in several fields such as biological microscopy, lithography, and multidomain optimization in optical systems.

Journal Article↗

PubMed2005

Face recognition by using feature-specific imaging.

We present a face-recognition system based on the optical measurement of linear features. We describe a polarization-based optical system that computes linear projections of an incident irradiance distribution. We quantify the fundamental limitations of optical feature measurement. We find that higher feature fidelity can be obtained by feature-specific imaging than by postprocessing a conventional image. We present feature-fidelity results for wavelet, principal component, and Fisher features. We study face recognition by using a k-nearest neighbors classifier and two different feed-forward neural networks. Each image block is reduced to either a one- or a two-dimensional feature space for input to these recognition algorithms. As high as 99% recognition has been achieved with one-dimensional wavelet feature projections and 100% has been achieved with two-dimensional projections. A 95-fold increase in noise tolerance by use of feature-specific imaging has been demonstrated for an example of the face-recognition problem. An optical experiment is performed to validate these results.

Algorithms↗

PubMed2005

High-resolution volume holographic profilometry using the Viterbi algorithm.

We use the Viterbi decoding algorithm to resolve depth features beyond the nominal resolution limit of a volume holographic profilometry system. The formulation treats the truncated point-spread function as an intersymbol interference and uses surface constraints and transition constraints to reduce the computational complexity. A factor-of-5 improvement in resolution was obtained in our experimental demonstration.

Journal Article↗

PubMed2005

Fast causal information transmission in a medium with a slow group velocity.

It is widely believed that the velocity of information upsiloni encoded on an optical pulse is equal to the group velocity upsilong, at least when upsilong is less than the speed of light in vacuum c. On the other hand, several authors suggest that upsiloni=c, although the size of the signal traveling at this velocity may be small, thereby making it difficult to measure. Here, we measure upsiloni for pulses propagating through a resonant "slow-light" medium where upsilong approximately 0.006c. We find upsiloni=1.03c(+0.49c)-0.25c, or that upsiloni approximately 168upsilong, clearly demonstrating that the speed of information cannot be generally described by upsilong, but is characterized by its own velocity.

Journal Article↗

PubMed2003

Efficient storage and transmission of ladar imagery.

We develop novel methods for compressing volumetric imagery that has been generated by single-platform (mobile) range sensors. We exploit the correlation structure inherent in multiple views in order to improve compression efficiency. We show that, for lossless compression, three-dimensional volumes compress more efficiently than two-dimensional (2D) images by a factor of 60%. Furthermore, our error metric for lossy compression suggests that accumulating more than nine range images in one volume before compression yields as much as a 99% improvement in compression performance over 2D compression.

Journal Article↗

PubMed2003

The speed of information in a 'fast-light' optical medium.

One consequence of the special theory of relativity is that no signal can cause an effect outside the source light cone, the space-time surface on which light rays emanate from the source. Violation of this principle of relativistic causality leads to paradoxes, such as that of an effect preceding its cause. Recent experiments on optical pulse propagation in so-called 'fast-light' media--which are characterized by a wave group velocity upsilon(g) exceeding the vacuum speed of light c or taking on negative values--have led to renewed debate about the definition of the information velocity upsilon(i). One view is that upsilon(i) = upsilon(g) (ref. 4), which would violate causality, while another is that upsilon(i) = c in all situations, which would preserve causality. Here we find that the time to detect information propagating through a fast-light medium is slightly longer than the time required to detect the same information travelling through a vacuum, even though upsilon(g) in the medium vastly exceeds c. Our observations are therefore consistent with relativistic causality and help to resolve the controversies surrounding superluminal pulse propagation.

Journal Article↗

PubMed2003

Feature-specific imaging.

We analyze the performance of feature-specific imaging systems. We study incoherent optical systems that directly measure linear projects of the optical irradiance distribution. Direct feature measurement exploit, the multiplex advantage, and for small numbers of projections can provide higher feature-fidelity than those systems that postprocess a conventional image. We examine feature-specific imaging using Wavelet, Karhunen-Loeve (KL), Hadamard, and independent-component features, quantifying feature fidelity in Gaussian-, shot-, and quantization-noise environments. An example of feature-specific imaging based on KL projections is analyzed and demonstrates that within a high-noise environment it is possible to improve image fidelity via direct feature measurement. A candidate optical system is presented and a preliminary implementational study is undertaken.

Journal Article↗

PubMed2003

Experimental demonstration of gray-scale sparse modulation codes in volume holographic storage.

We discuss experimental results of a versatile nonbinary modulation and channel code appropriatefor two-dimentional page-oriented holographic memories. An enumerative permutation code is used to provide a modulation code that permits a simple maximum-likelihood detection scheme. Experimental results from the IBM Demon testbed are used to characterize the performance and feasibility of the proposed modulation and channel codes. A reverse coding technique is introduced to combat the effects of error propagation on the modulation-code performance. We find experimentally that level-3 pixels achieve the beet practical result, offering an 11-35% improvement in capacity and a 12% increase in readout rate as compared with local binary thresholding techniques.

Journal Article↗

PubMed2002

Parallel image restoration with a two-dimensional likelihood-based algorithm.

We describe a pixelwise parallel algorithm for the restoration of images that have been corrupted by a low-pass optical channel and additive noise. This new algorithm is based on an iterative soft-decision method of error correction (i.e., turbo decoding) and offers performance on binary-valued imagery that is comparable to the Viterbi algorithm. We quantify the restoration performance of this new algorithm on random binary imagery for which it is superior to both the Wiener filter and the projection onto convex sets algorithms over a wide range of channels. For typical optical channels, the new algorithm is within 0.5 dB of the two-dimensional Viterbi restoration method [J. Opt. Soc. Am. A 17, 265 (2000)]. We also demonstrate the extension of our new algorithm to correlated and gray-scale images using vector quantization to mitigate the associated complexity burden. A highly parallel focal-plane implementation is also discussed, and a design study is presented to quantify the capabilities of such a VLSI hardware solution. We find that video-rate restoration on 252 x 252 pixel images is possible using current technology.

Journal Article↗