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Multispectral Transmission Map Fusion Method and Architecture for Image Dehazing

机译:图像去雾的多光谱透射图融合方法及架构

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摘要

Image dehazing is an essential preprocessing stage for several applications such as surveillance, long-range imaging, automatic driver-assistance system (ADAS), and remote sensing. Haze particles degrade visible-band images more severely than the infrared images due to scattering phenomena. Therefore, infrared data can be effectively utilized to enhance the visibility of color images captured in a hazy environment. In this brief, for the first time, a multispectral transmission map fusion approach is presented, wherein a haze-aware weight generation scheme is used to improve transmission map in specific regions. This achieves significant quantitative improvement as compared with the existing methods. In addition, the method is extremely suitable for hardware implementation. Therefore, a low-cost very large-scale integration (VLSI) architecture is also presented. The application-specified integrated circuit (ASIC) and field-programmable gate array (FPGA) implementations dissipate 3.45- and 57-mW power at 150 MHz, respectively. Both ASIC and FPGA achieve a high throughput of 450 and 308 Mpixels/s, respectively. The design does not require any external memory such as dynamic random access memory, thus making it suitable for on-chip processing that can be closely integrated with an image sensor.
机译:图像去雾是用于多种应用程序(例如监视,远程成像,自动驾驶辅助系统(ADAS)和遥感)的必不可少的预处理阶段。由于散射现象,雾度粒子比红外图像更严重地破坏可见光带图像。因此,可以有效地利用红外数据来增强在朦胧环境中捕获的彩色图像的可见性。在本摘要中,首次提出了一种多光谱传输图融合方法,其中使用了雾度感知权重生成方案来改进特定区域中的传输图。与现有方法相比,这实现了显着的定量改进。另外,该方法非常适合硬件实现。因此,还提出了一种低成本的超大规模集成(VLSI)体系结构。专用集成电路(ASIC)和现场可编程门阵列(FPGA)实现分别在150 MHz时耗散3.45和57 mW的功率。 ASIC和FPGA均分别达到450和308 Mpixels / s的高吞吐量。该设计不需要任何外部存储器,例如动态随机存取存储器,因此使其适用于可以与图像传感器紧密集成的片上处理。

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