Fixed Pattern Noise Suppression Algorithm Based on Background Modeling

Tang, Huang; Liu, Xiaolin; Shen, Yang

doi:10.1016/j.proeng.2012.01.059

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…They can traditionally yield better results than calibration-based techniques, especially when the operating conditions of the sensor cannot be correctly approximated by a simple combination of the calibration measurements. It is obvious that such techniques increase system reliability but have higher computational complexity [35] requiring significant hardware resources to be processed at the sensor frame rate.…”

Section: Dynamic Fpn Estimation By Scene-based Methodsmentioning

confidence: 99%

Scene-based non-uniformity correction: From algorithm to implementation on a smart camera

Toczek¹,

Hamdi²,

Heyrman³

et al. 2013

Journal of Systems Architecture

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Section: Dynamic Fpn Estimation By Scene-based Methodsmentioning

confidence: 99%

Scene-based non-uniformity correction: From algorithm to implementation on a smart camera

Toczek¹,

Hamdi²,

Heyrman³

et al. 2013

Journal of Systems Architecture

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“…They are able to yield better results than calibration-based techniques. This method has higher machine reliability but higher computational complexity [16]. Scene-based non-uniformity correction (NUC) methods include distinct classes of postprocessing-algebraic techniques, and statistical techniques.…”

Section: Related Workmentioning

confidence: 99%

Scene based Non-uniformity Correction for Optical Remote Sensing Imagery

Gopan¹,

Venkateswarlu²,

Nair³

et al. 2017

IJIGSP

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Abstract-In this work, we propose and evaluate different scene based methods for non-uniformity corrections for optical remote sensing data sets. These methods can be used to correct or refine the existing radiometric calibrations, thereby improving the image quality. The performance of each algorithm against different datasets are analyzed and a quantitative comparison of different quality parameters viz. entropy, correlation coefficient, signal to noise ratio, peak signal to noise ratio and structural similarity index are carried out to recommend the best method for each scene. For a given data set, the selected method depends on the severity, type of terrain it covered, etc.

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“…FPN is dynamically updated from the real-time analysis of the scenes captured by the sensor. It is obvious that such techniques increase system reliability but have higher computational complexity [7] requiring significant hardware resources to be processed at the sensor frame rate. Scene-based methods include two distinct categories: (1) algebraic techniques, and (2) statistical techniques.…”

Section: Introductionmentioning

confidence: 99%

Scene-based noise reduction on a smart camera

Hamdi

Toczek

Heyrman

et al. 2012

2012 19th IEEE International Conference on Electronics, Circuits, and Systems (ICECS 2012)

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Abstract-Raw output data from CMOS image sensors tends to exhibit significant noise called Fixed-Pattern Noise (FPN) due to on-die variations between pixel photodetectors. FPN is often corrected by subtracting its value, estimated through calibration, from the sensor's raw signal. This paper introduces an on-line scene-based technique for an improved FPN compensation which does not rely on calibration, and hence is more robust to the dynamic changes in the FPN which may occur slowly over time. Development has been done with a special emphasis on realtime hardware implementation on a FPGA-based smart camera. Experimental results on different scenes are depicted showing that the proposed correction chain induces little additional resource use while guarantying high quality images.

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Fixed Pattern Noise Suppression Algorithm Based on Background Modeling

Cited by 3 publications

References 4 publications

Scene-based non-uniformity correction: From algorithm to implementation on a smart camera

Scene-based non-uniformity correction: From algorithm to implementation on a smart camera

Scene based Non-uniformity Correction for Optical Remote Sensing Imagery

Scene-based noise reduction on a smart camera

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