A design of real-time scene-based nonuniformity correction system

Mou, Xingang; Zhang, Guilin; Hu, Ruofei

doi:10.1117/12.833899

Cited by 3 publications

(5 citation statements)

References 11 publications

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“…Xingang [11] proposes an FPGA implementation of a NUC neural network with an adaptive learning rate based on image edge content with comparable result. However, our network uses significantly fewer hardware resources and can implement the entire algorithm on a single FPGA, whereas Xingang's approach requires the use of a DSP to implement complex computations.…”

Section: Resultsmentioning

confidence: 99%

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FPGA-based Neural Network for Nonuniformity Correction on Infrared Focal Plane Arrays

Celedon

Redlich

Figueroa

2012

2012 15th Euromicro Conference on Digital System Design

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Despite recent technological advances which improve their performance and reduce their cost, Focal Plane Arrays for infrared imagers suffer from spatial nonuniformity that renders their output unusable unless a suitable correction method is applied. This paper describes an embedded hardware implementation of Scribner's algorithm for online nonuniformity correction. Our implementation on a Xilinx Spartan XC3S1200E FPGA achieves a throughput of more than 130 frames per second on 320×240-pixel IR video, which greatly exceeds realtime requirements. The power consumption of our system is 329mW, which is two orders of magnitude smaller than a software implementation of the algorithm on a traditional processor, and can be greatly reduced with a custom-VLSI implementation of the architecture. 2012 15th Euromicro Conference on Digital System Design 978-0-7695-4798-5/12 $26.00

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Section: Resultsmentioning

confidence: 99%

“…Performing the algebraic manipulation in the error equation (11), it is possible to avoid computing the division by the constant 49. Therefore, the module Hidden Layer performs only the summation in the neighborhood of each pixel in the image.…”

Section: B Hidden Layer Modulementioning

confidence: 99%

FPGA-based Neural Network for Nonuniformity Correction on Infrared Focal Plane Arrays

Celedon

Redlich

Figueroa

2012

2012 15th Euromicro Conference on Digital System Design

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“…Machine learning techniques implementations in FPGAs include in this paper neural networks, genetic algorithms, support vector machine, spiking neural network and AdaBoost. These have been implemented for image processing [527,1582,1583], pattern recognition [476,1584], real-time processing [671,1477,1585], melanoma cancer detection [510,511,1586,1587], speech recognition [1587,1588] and so forth. Digital signal processing techniques implementations in FPGAs covers FFT [537,[1589][1590][1591][1592][1593], DWT [597,[1594][1595][1596][1597], time-to-digital converters [1598][1599][1600][1601][1602], DCT [580,[1603][1604][1605] and digital filters like FIR filter [56,612,[1606][1607][1608], Kalman filter [620,[1609][1610][1611], median filter [1612,…”

Section: Discussionmentioning

confidence: 99%

“…In the red cluster, we find FPGAs' applications focused in real-time implementations, such as data acquisition [565,[1473][1474][1475], simulations [1022,1024,1082,1476], Neural Netw. [1477][1478][1479] and image processing [1480][1481][1482][1483][1484][1485][1486][1487]. Finally, the blue cluster shows that the fault tolerance and high reliability systems are based in fault injection impelmentations [1488,1489] and single event upset tolerance mechanisms [1490][1491][1492].…”

Section: Applications Mappingmentioning

confidence: 99%

Field Programmable Gate Array Applications—A Scientometric Review

2019

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Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications.

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“…Scene-based nonuniformity correction algorithms are widely used since they only need the readout image data. Mou et al [20] proposed a method based on the neural network algorithm for real-time correction using the framework of foreground and background. Wen et al [21] proposed a novel binarization method for nonuniformly illumination based on the curvelet transform.…”

Section: Introductionmentioning

confidence: 99%

Nonuniform Background Correction for Wide-Field Surveillance Camera

Zhou

Wang

2023

Applied Sciences

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Space environment surveillance is very important for space security, which is easy to be disturbed by stray light and hot pixels, and the image background presents a certain degree of nonuniformity. The existing methods can not achieve the accurate segmentation of weak targets while correcting the nonuniform background. To solve this problem, this paper presents an accurate and robust correction method for the wide-field surveillance camera, called the enhanced new top-hat transform (ENTHT). Firstly, we analyze the formation mechanism and influence of the nonuniformity background from multiple dimensions. Secondly, because of the dependence and limitations of the background suppression effect of the new top-hat transform on the selection of structural elements, we improve the new top-hat transform by designing a noise structure element (NSE). Finally, we analyze the performance and advantages of the ENTHT method. In the field experiment, the method can accurately correct the complex space nonuniform background, eliminate the stray light and hot pixels, and realize the accurate segmentation of weak targets. In the complex space environment, it brings great help to space-moving target recognition and tracking.

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A design of real-time scene-based nonuniformity correction system

Cited by 3 publications

References 11 publications

FPGA-based Neural Network for Nonuniformity Correction on Infrared Focal Plane Arrays

FPGA-based Neural Network for Nonuniformity Correction on Infrared Focal Plane Arrays

Field Programmable Gate Array Applications—A Scientometric Review

Nonuniform Background Correction for Wide-Field Surveillance Camera

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