Nonlinear Systems for Image Processing

Morfu, Savério; Marquié, Patrick; Nofiele, B.; Ginhac, Dominique

doi:10.1016/s1076-5670(08)00603-4

Cited by 28 publications

(37 citation statements)

References 109 publications

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“…A method of network's research was used the same as in [22]. To find the dependence V n,k (t) we have solved a system of N= N x *N y = 4056 ordinary differential equations (3) …”

Section: S-shapedmentioning

confidence: 99%

Quasiperiodic AlGaAs superlattices for neuromorphic networks and nonlinear control systems

Malyshev

2015

Journal of Applied Physics

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“…A method of network's research was used the same as in [22]. To find the dependence V n,k (t) we have solved a system of N= N x *N y = 4056 ordinary differential equations (3) …”

Section: S-shapedmentioning

confidence: 99%

Quasiperiodic AlGaAs superlattices for neuromorphic networks and nonlinear control systems

Malyshev

2015

Journal of Applied Physics

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“…The stability analysis of the two systems (4) and (7) depends respectively on the considered nonlinear forces f and g, the potentials they derive from being represented in figure 4.(b). This analysis being presented in details in Morfu et al (2008), we just present here some remarks allowing to understand the dynamics of our system:…”

Section: Image Processing Applications 221 Image Segmentationmentioning

confidence: 99%

On Some Applications of Nonlinear Differential Equations in Image Processing: Concepts and Electronic Implementation

Morfu¹,

Marquié²

2011

Applications and Experiences of Quality Control

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“…CMOS image sensors are well-know to be prone to noise, especially under low illumination conditions [1]- [3]. Among them, Fixed-Pattern Noise (FPN) is the pixel-to-pixel output variation under uniform illumination due to mismatched pixels and associating readout circuits [4].…”

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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Nonlinear Systems for Image Processing

Cited by 28 publications

References 109 publications

Quasiperiodic AlGaAs superlattices for neuromorphic networks and nonlinear control systems

Quasiperiodic AlGaAs superlattices for neuromorphic networks and nonlinear control systems

On Some Applications of Nonlinear Differential Equations in Image Processing: Concepts and Electronic Implementation

Scene-based noise reduction on a smart camera

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