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Infrared detectors: status and trends

Find the most up-to-date and comprehensive treatment of classical and modern antennas and their related technologies in Modern Antenna Handbook. Have access to current theories and practices in the field of antennas, with topics like metamaterials, microelectromechanical systems (MEMS), frequency selective surfaces (FSS), radar cross sections (RCS), and advanced numerical and computational methods targeted primarily for the analysis and design of antennas. Written by leading international experts, this book will help you understand recent developments in antenna-related technology and the future direction of this fast-paced field.

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Modern Antenna Handbook

Neural remodeling in retinal degeneration.

Infrared detectors: an overview

This paper describes the development of a high-density electronic interface to the central nervous system. Silicon micromachined electrode arrays now permit the long-term monitoring of neural activity in vivo as well as the insertion of electronic signals into neural networks at the cellular level. Efforts to understand and engineer the biology of the implant/tissue interface are also underway. These electrode arrays are facilitating significant advances in our understanding of the nervous system, and merged with on-chip circuitry, signal processing, microfluidics, and wireless interfaces, they are forming the basis for a family of neural prostheses for the possible treatment of disorders such as blindness, deafness, paralysis, severe epilepsy, and Parkinson's disease.

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Wireless implantable microsystems: high-density electronic interfaces to the nervous system

Retinal Prosthesis for the Blind

Requirements for infrared focal plane arrays (IRFPAs) for advanced infrared imaging systems are discussed, and an overview is given of different IRFPA architectures. Important IR detector structures, including photoconductive, photovoltaic, metal-insulator-semiconductor (MIS), and Schottky barrier, are reviewed. Infrared detector materials and related crystal-growth techniques are discussed, emphasizing applicability to IRFPA designs and performance. Three types of input circuit used to couple the detector to the readout circuitry are discussed, namely, direct injection, buffered direct injection, and gate modulation. An overview is given of several readout techniques, including the CCD, MOSFET switch, CID, and CIM. Also discussed are related onchip signal processing topics as well as questions regarding producibility and array implementation. >

Infrared focal plane array technology

With rapid advancements in infrared focal plane array (IRFPA) technology, greater demands are being placed on nonuniformity correction (NUC) techniques to provide near-BLIP performance over a wide dynamic range. Standard NUC techniques involve calibrating each detector using reference temperature sources before imaging the IRFPA. Usually the correction needs to be re-calibrated after a short period of time due to IRFPA drift or to adjust for changes in the level of background flux. Adaptive NUC techniques eliminate the need for calibration by continuously updating the correction coefficients based on radiance levels of the scene being viewed. In this manner, continuous compensation can be applied adaptively for individual detector non-idealities and background changes. Two adaptive NUC techniques are discussed; one is a temporal highpass filter and the other involves a neural network with lateral interconnects to nearest neighbor pixels. Both have similarities to biological retinal processing. Questions of implementation and stability are discussed and performance results are given for several test image sequences which were obtained from an MWIR HgCdTe array and a HIDAD uncooled array. We conclude that adaptive techniques will be very useful in future IRFPA sensors, primarily because of their ability to adapt over a wide range of background flux without calibration sources, but also because they can offer improved sensitivity under most operating conditions.

Adaptive nonuniformity correction for IR focal-plane arrays using neural networks

Scene-based nonuniformity correction (NUC) was performed via two techniques, and the results are presented in terms of ability to allow increased sensitivity and to minimize scene degradation. The two techniques perform recalibration in real-time based on the radiance levels of the scene being viewed. The scene-based NUC was effected with an algorithm based on a temporal high-pass filter, and with one based on an artificial neural network. Recorded data from an MWIR staring array collecting different images were used for the experiments. The advantages of the two scene-based NUC techniques are summarized and compared to those of the traditional calibration technique. The potential for the elimination of spatial noise and the achievement of BLIP performance levels in high-quantum-efficiency FPAs are emphasized. Spatial noise can be eliminated by employing real-time signal processors.

Nonuniformity correction for staring IR focal plane arrays using scene-based techniques

Retina-like processing techniques to perform nonuniformity correction of infrared focal plane arrays (IRFPAs) are discussed. The objective is to design and test electronic structures based on early vision processes in the vertebrate retina. Two adaptive techniques are successfully developed. Both are stable and convergent and are used to process existing infrared images in nonreal time on the Naval Research Laboratory (NRL) Connection Machine. They are implemented on a real-time image array processor interfaced to an IRFPA in the laboratory. Conceptual designs for an analog chip are prepared and partially simulated. >

Dean A. Scribner

Papers

Retinal Prosthesis for the Blind

Infrared focal plane array technology

Adaptive nonuniformity correction for IR focal-plane arrays using neural networks

Nonuniformity correction for staring IR focal plane arrays using scene-based techniques

Adaptive retina-like preprocessing for imaging detector arrays