A model of visual adaptation for realistic image synthesis
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Communications of the ACM
Two-Dimensional Digital Signal Processing II: Transforms and Median Filters
Two-Dimensional Digital Signal Processing II: Transforms and Median Filters
A Variational Framework for Retinex
International Journal of Computer Vision
Research on Image Median Filtering Algorithm and Its FPGA Implementation
GCIS '09 Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03
Theory and Applications of Digital Speech Processing
Theory and Applications of Digital Speech Processing
A Separable Median Filter for Image Noise Smoothing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Retinex by two bilateral filters
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Tuning the smoothness of the recursive median filter
IEEE Transactions on Signal Processing
Stochastic analysis for the recursive median filter process
IEEE Transactions on Information Theory
Dynamic range compression based on illumination compensation
IEEE Transactions on Consumer Electronics
High fidelity color reproduction of plasma displays under ambient lighting
IEEE Transactions on Consumer Electronics
IEEE Transactions on Consumer Electronics
Properties and performance of a center/surround retinex
IEEE Transactions on Image Processing
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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.