Infrared focal plane array technology

Scribner, Dean A.; Kruer, M.; Killiany, J. M.

doi:10.1109/5.64383

Cited by 215 publications

(98 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Traditional NUC algorithms are based on the calibration [1,4], which determine the parameters of the mapping by inserting extended source blackbodies into the optical path and recording the responses at one or more background temperatures. However, the nonuniformity or FPN is always influenced by external conditions such as ambient temperature, variation in the transistor bias voltage [5][6][7]. This results in that the response of each detector drifts slowly with the time lapse.…”

Section: Introductionmentioning

confidence: 96%

See 1 more Smart Citation

A scene-based nonuniformity correction algorithm based on fuzzy logic

Huang

Fan

et al. 2015

Opt Rev

View full text Add to dashboard Cite

Scene-based nonuniformity correction algorithms based on the LMS adaptive filter are quite efficient to reduce the fixed pattern noise in infrared images. They are famous for their low cost of computation and storage recourses. Unfortunately, ghosting artifacts can be easily introduced in edge areas when the inter-frame motion slows. In this paper, a gated scene-based nonuniformity correction algorithm is proposed. A novel low-pass filter based on the fuzzy logic is proposed to estimate the true scene radiation as the desired signal in the LMS adaptive filter. The fuzzy logic can also evaluate the probability that a pixel and its locals belong to edge areas. Then the update of the correction parameters for the pixels in edge areas can be gated. The experiment results show that our method is reliable and the ghosting artifacts are reduced.

show abstract

Section: Introductionmentioning

confidence: 96%

“…Rotation, scaling, and other nonrigid transformations [17][18][19][20] are ignored. The third class is based on the neural network [5,6,8,9,21], which adaptively determines the parameters of the nonunifomity model according to ''desired'' images that are formed by low-pass filters.…”

Section: Introductionmentioning

confidence: 99%

A scene-based nonuniformity correction algorithm based on fuzzy logic

Huang

Fan

et al. 2015

Opt Rev

View full text Add to dashboard Cite

show abstract

“…The increased background flux eases the electronic noise requirements on the focal-plane readout due to an increased background shot noise. However, a conventional reset-integrator type readout [5,6] integrates the entire background flux in the unit cell, thereby imposing prohibitively large dynamic range requirements on the readout pixel (required storage capacity ~ 10 9 carriers per pixel). The effective dynamic range requirement can be reduced a factor of N if an N-fold suppression of the background flux is achieved on the focal-plane.…”

Section: Advantages Of Background Suppressionmentioning

confidence: 99%

Low-power low-noise analog circuits for on-focal-plane signal processing of infrared sensors

et al. 1993

View full text Add to dashboard Cite

On-focal-plane signal processing circuits for enhancement of IR imager performance are presented. To enable the detection of high background IR images, an in-pixel current-mode background suppression scheme is presented. The background suppression circuit consists of a current memory placed in the feedback loop of a CTIA and is designed for a thousand-fold suppression of the background flux, thereby easing circuit design constraints, and assuring BLIP operation even with detectors having large response non-uniformities. For improving the performance of low-background IR imagers, an onchip column-parallel analog-to-digital converter (ADC) is presented. The design of a 10-bit ADC with 50 µm pitch and based on sigma-delta (Σ-∆) modulation is presented. A novel IR imager readout technique featuring photoelectron counting in the unit cell is presented for ultra-low background applications. The output of the unit cell is a digital word corresponding to the incident flux density and the readout is noise free. The design of low-power (< 5 µW), sub-electron input-referred noise, high-gain (> 100,000), small real-estate (60 µm pitch) self-biased CMOS amplifiers required for photon counting are presented.

show abstract

“…An FPA consists of a number of photodiode sets that convert thermal energy into electric signals inside the IR detector. 1,2 When an FPA is used in an IR detector, its output can have nonuniformity problems if the response characteristic of each photodiode is different. This causes fixed pattern noise (FPN) in IR images, degrading the image quality significantly.…”

Section: Introductionmentioning

confidence: 99%

Nonuniformity correction scheme considering the effects of internal thermal stray light

Kim

Chang

2017

Opt. Eng

View full text Add to dashboard Cite

Abstract. A stray light compensated nonuniformity correction (SLCNUC) method is proposed for infrared (IR) cameras. The proposed approach formulates thermal stray light compensation functions according to the internal temperature changes of the IR camera. To derive the compensation functions, we analyze the variations of the NUC parameters over the entire range of internal temperatures and determine the function coefficients by using a least squares method. Compared with the existing NUC methods used in previous studies, the major advantage of the proposed method is its effective reduction of nonuniformity even in highly accumulated thermal stray light situations. Experiments and comparisons performed with real IR images show that the proposed method maintains lower spatial noise over a wide internal temperature range of the IR camera. It is shown that the proposed NUC achieves an 18 dB higher peak signal-to-noise ratio than that of the conventional reference-based NUC method. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

show abstract

Infrared focal plane array technology

Cited by 215 publications

References 82 publications

A scene-based nonuniformity correction algorithm based on fuzzy logic

A scene-based nonuniformity correction algorithm based on fuzzy logic

Low-power low-noise analog circuits for on-focal-plane signal processing of infrared sensors

Nonuniformity correction scheme considering the effects of internal thermal stray light

Contact Info

Product

Resources

About