• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.813-818
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• 2021

This paper proposes an optimized hardware implementation method for existing CIE1931 color gamut control algorithm. Among the post-processing methods of dehazing algorithms, existing algorithm with relatively low computations have the disadvantage of consuming many hardware resources by calculating large bits using Split multiplier in the computation process. The proposed algorithm achieves computational reduction and hardware miniaturization by reducing the predefined two matrix multiplication operations of the existing algorithm to one. And by optimizing the Split multiplier computation, it is implemented more efficient hardware to mount. The hardware was designed in the Verilog HDL language, and the results of logical synthesis using the Xilinx Vivado program were compared to verify real-time processing performance in 4K environments. Furthermore, this paper verifies the performance of the proposed hardware with mounting results on two FPGAs.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.