Nonlinear Systems for Image Processing

Advances in imaging and electron physics
Source: OAI

ABSTRACT Nonlinear Systems for Image Processing

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    ABSTRACT: This paper describes a complete FPGA-based smart camera architecture named HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) which produces a real-time high dynamic range (HDR) live video stream from multiple captures. A specific memory management unit has been defined to adjust the number of acquisitions to improve HDR quality. This smart camera is built around a standard B&W CMOS image sensor and a Xilinx FPGA. It embeds multiple captures, HDR processing, data display and transfer, which is an original contribution compared to the state-of-the-art. The proposed architecture enables a real-time HDR video flow for a full sensor resolution (1.3 Mega pixels) at 60 frames per second.
    Journal of Real-Time Image Processing 01/2014; DOI:10.1007/s11554-013-0393-7 · 1.11 Impact Factor
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    ABSTRACT: It is progressively realized that noise can play a constructive role in the domain of nonlinear information pro-cessing. This phenomenon, also known as stochastic resonance (SR) effect, has experienced large varieties of extensions with variations concerning the type of noise, the type of information carrying signal or the type of nonlinear system interacting with the signal-noise mixture. In this article, we propose an interpretation for the mechanism of noise-enhanced image restoration with nonlinear PDE (Partial Differential Equation) recently demonstrated in literature. More precisely, a link is established between the action of noise in a nonlinear Perona–Malik anisotropic diffusion and stochastic resonance in memoryless nonlinear systems for 1-D signals. For illustration some preliminary results are presented on classical "camera-man" image and the inner of SR mechanism is theoretically and practically studied using a simple set of parameters regarding the PDE used and the modeling of boundaries within images.
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    ABSTRACT: We demonstrate a new instance of useful-noise effect or stochastic resonance, occurring in magnetic resonance imaging (MRI). Based on the physics of signal–noise coupling specific to MRI, we establish the possibility of regimes where nonlinear post-processing can benefit from an increase in the level of the noise present in the MRI apparatus. The validation is obtained by both theoretical analysis and experimental observations. We especially show that the beneficial tuning of the noise can be practically achieved by controlling the bandwidth of the sampling receiver of the MRI apparatus. These results constitute a nontrivial extension of stochastic resonance in the domain of images, arising here with a signal–noise coupling in MRI which is distinct from the purely additive or multiplicative couplings previously investigated in the framework of useful-noise effect.
    Fluctuation and Noise Letters 04/2013; 12(01). DOI:10.1142/S0219477513500053 · 0.77 Impact Factor

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May 20, 2014