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A Fast Defogging Image Recognition Algorithm Based on Bilateral Hybrid Filtering

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Published:21 April 2021Publication History
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Abstract

With the rapid advancement of video and image processing technologies in the Internet of Things, it is urgent to address the issues in real-time performance, clarity, and reliability of image recognition technology for a monitoring system in foggy weather conditions. In this work, a fast defogging image recognition algorithm is proposed based on bilateral hybrid filtering. First, the mathematical model based on bilateral hybrid filtering is established. The dark channel is used for filtering and denoising the defogging image. Next, a bilateral hybrid filtering method is proposed by using a combination of guided filtering and median filtering, as it can effectively improve the robustness and transmittance of defogging images. On this basis, the proposed algorithm dramatically decreases the computation complexity of defogging image recognition and reduces the image execution time. Experimental results show that the defogging effect and speed are promising, with the image recognition rate reaching to 98.8% after defogging.

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    • Published in

      cover image ACM Transactions on Multimedia Computing, Communications, and Applications
      ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 17, Issue 2
      May 2021
      410 pages
      ISSN:1551-6857
      EISSN:1551-6865
      DOI:10.1145/3461621
      Issue’s Table of Contents

      Copyright © 2021 ACM

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      Publication History

      • Published: 21 April 2021
      • Revised: 1 October 2020
      • Online AM: 7 May 2020
      • Accepted: 1 March 2020
      • Received: 1 June 2019
      Published in tomm Volume 17, Issue 2

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