Abstract: Digital cameras, new generation phones, commercial TV sets and, in general, all modern devices for image acquisition and visualization can benefit from algorithms for image enhancement suitable to work in real time and preferably with limited power consumption. Among the various methods described in the scientific literature, Retinex-based approaches are able to provide very good performances, but unfortunately they typically require a high computational effort. In this article, we propose a flexible and effective architecture for the real-time enhancement of video frames, suitable to be implemented in a single FPGA device. The video enhancement algorithm is based on a modified version of the Retinex approach. This method, developed to control the dynamic range of poorly illuminated images while preserving the visual details, has been improved by the adoption of a new model to perform illuminance estimation. The video enhancement parameters are controlled in real time through an embedded microprocessor which makes the system able to modify its behavior according to the characteristics of the input images, and using information about the surrounding light conditions.

A flexible FPGA implementation for illuminance–reflectance video enhancement

MARSI, STEFANO;RAMPONI, GIOVANNI
2011-01-01

Abstract

Abstract: Digital cameras, new generation phones, commercial TV sets and, in general, all modern devices for image acquisition and visualization can benefit from algorithms for image enhancement suitable to work in real time and preferably with limited power consumption. Among the various methods described in the scientific literature, Retinex-based approaches are able to provide very good performances, but unfortunately they typically require a high computational effort. In this article, we propose a flexible and effective architecture for the real-time enhancement of video frames, suitable to be implemented in a single FPGA device. The video enhancement algorithm is based on a modified version of the Retinex approach. This method, developed to control the dynamic range of poorly illuminated images while preserving the visual details, has been improved by the adoption of a new model to perform illuminance estimation. The video enhancement parameters are controlled in real time through an embedded microprocessor which makes the system able to modify its behavior according to the characteristics of the input images, and using information about the surrounding light conditions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2494938
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