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http://dx.doi.org/10.6109/jkiice.2021.25.6.819

Hardware Implementation of Fog Feature Based on Coefficient of Variation Using Normalization  

Kang, Ui-Jin (Department of Electronics Engineering, Dong-A University)
Kang, Bong-Soon (Department of Electronics Engineering, Dong-A University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.6, 2021 , pp. 819-824 More about this Journal
Abstract
As technologies related to image processing such as autonomous driving and CCTV develop, fog removal algorithms using a single image are being studied to improve the problem of image distortion. As a method of predicting fog density, there is a method of estimating the depth of an image by generating a depth map, and various fog features may be used as training data of the depth map. In addition, it is essential to implement a hardware capable of processing high-definition images in real time in order to apply the fog removal algorithm to actual technologies. In this paper, we implement NLCV (Normalize Local Coefficient of Variation), a feature of fog based on coefficient of variation, in hardware. The proposed hardware is an FPGA implementation of Xilinx's xczu7ev-2ffvc1156 as a target device. As a result of synthesis through the Vivado program, it has a maximum operating frequency of 479.616MHz and shows that real-time processing is possible in 4K UHD environment.
Keywords
Single image; Fog features; 4K UHD; Real time processing; Hardware implementation;
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