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Volume 56 Issue 1
Jan.  2021
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Journal of Southwest Jiaotong University  > 2021  >  56(1): 160-167, 205.
GUO Nan, CHEN Zhenghan, YANG Xiaohui, GUO Jianfeng, SUN Shuguo. Mechanical Properties and Water Holding Characteristics of Initially Isotropic Soils and Transversely Isotropic Soils[J]. Journal of Southwest Jiaotong University, 2019, 54(6): 1235-1243. doi: 10.3969/j.issn.0258-2724.20180065
Citation: WANG Jian, QIN Chunxia, YANG Ke, REN Ping, ZHENG Jie, ZHAO Yuanpeng, CHEN Guifeng. Design of Airborne Video Dehazing System for UCAV Based on HSV Transmission Weighted Correction[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 160-167, 205. doi: 10.3969/j.issn.0258-2724.20190985
shu

Design of Airborne Video Dehazing System for UCAV Based on HSV Transmission Weighted Correction

doi: 10.3969/j.issn.0258-2724.20190985
  • Received Date: 12 Oct 2019
  • Rev Recd Date: 16 Mar 2020
    • Available Online: 08 Apr 2020
  • Publish Date: 01 Feb 2021
    Abstract
  • As there is image degradation when the UCAV (unmanned combat air vehicle) captures the real-time image in the haze day, a low power-consumption system is designed on the basis of the HSV (hue, saturation, value) transmission weighted correction. First, the overall design of the dehazing system is completed, which can meet the requests of a low power-consumption and real-time image dehazing. Then, according to the needs of the video acquisition dehazing system, functions are being designed, including digital video BT.656/BT.1120 interlaced and progressive processing, video control, instruction receiving processing, TS1601 video dehazing algorithm processing, H.264 video compression processing and framing, etc. Lastly, the design and implementation are focused in terms of the system dehazing algorithm, platform design, dehazing parameter processing and other functional modules. Also this system and several other methods suggested in references are used to process typical hazy images respectively, and then evaluated after employing three definition evaluation functions (variance function, average gradient function and TenenGrad function) and normalization process. The results indicate that the design of this dehazing system has such merits as low power consumption, easy implementation, and high adaptability. After processing the typical hazy images, the variance function is increased by 46.87%, 1.44% and 12.83%, the average gradient function is increased by 12.54%, 9.26% and 11.15%, that of normalization of TenenGrad function is increased by 53.19%, 3.60% and 8.82%, respectively. The overall operation time of the test algorithm is respectively increased by 4.74 times, 5.41 times and 5.46 times.

     

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