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Fpga Implementation Of A Real-time Biologically Inspired Image Enhancement Algorithm

机译:实时生物启发图像增强算法的Fpga实现

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This paper presents an FPGA implementation of a novel image enhancement algorithm, which compensates for the under-/over-exposed image regions, caused by the limited dynamic range of contemporary standard dynamic range image sensors. The algorithm, which is motivated by the attributes of the shunting center-surround cells of the human visual system, is implemented in Altera Stratix II GX: EP2SGX130GF1508C5 FPGA device. The proposed implementation, which is synthesized in an FPGA technology, employs reconfigurable pipeline, structured memory management, and data reuse in spatial operations, to render in real-time the huge amount of input data that the video signal comprisees. It also avoids the use of computationally intensive operations, achieving the required specifications in terms of flexibility, timing, performance and visual quality. The proposed implementation allows real-time processing of color images with sizes up to 2.5 Mpixels, at frame rate of 25 fps. As a result, the architectural solution described in this work offers a low-cost implementation for automatic exposure correction in real-time video systems.
机译:本文介绍了一种新颖的图像增强算法的FPGA实现,该算法可补偿由于当代标准动态范围图像传感器的动态范围有限而引起的曝光不足/曝光过度的图像区域。该算法受人眼视觉系统的分流中心-环绕单元属性的影响,在Altera Stratix II GX:EP2SGX130GF1508C5 FPGA器件中实现。拟议的实现是在FPGA技术中综合而成的,在空间操作中采用了可重新配置的流水线,结构化的内存管理和数据重用,以实时呈现视频信号所包含的大量输入数据。它还避免了使用计算密集型运算,从而在灵活性,时序,性能和视觉质量方面达到了所需的规格。所提出的实现方式允许以25 fps的帧速率实时处理大小高达2.5 Mpixels的彩色图像。结果,本文中描述的体系结构解决方案为实时视频系统中的自动曝光校正提供了一种低成本的实现。

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