VLSI Implementation for an Adaptive Haze Removal Method

Yao Tsung Kuo, Wei Ting Chen, Pei Yin Chen, Cheng Hsien Li

研究成果: Article同行評審

14 引文 斯高帕斯(Scopus)

摘要

In the real-time outdoor application of computer vision-based systems, haze removal, a pre-processing technique that can recover clear images from foggy ones, is necessary for object detection. Therefore, in this paper, an efficient haze removal method suitable for hardware design is proposed to obtain high quality fog-free images. Based on the atmosphere scattering model and the dark channel prior method, the atmospheric light of the whole image and the transmission map could be extracted. These are important and necessary parameters of the recovery model. Instead of using single global atmospheric light to restore foggy image, a local atmospheric light estimation method is applied in the proposed design to achieve optimal results. To ensure that the overall image is consistent without block artifacts, dynamic adjustment of local atmospheric light is made based on global atmospheric light. Additionally, to obtain a transmission map, a refined estimation method is performed to ease the halo effect. In terms of both quantitative and qualitative evaluations, the simulation results indicate that the proposed design exhibits superior performance without color oversaturation and distortion. To meet the requirements of real-time applications, a six-stage very-large-scale integration (VLSI) architecture for the proposed algorithm is implemented by using TSMC 0.13-$\mu$ m technology. The synthesis results show that the design yields a processing rate of approximately 200 Mpixels/s, which is rapid enough to facilitate Full HD resolution at 30 fps in real time.

原文English
文章編號8903266
頁(從 - 到)173977-173988
頁數12
期刊IEEE Access
7
DOIs
出版狀態Published - 2019

All Science Journal Classification (ASJC) codes

  • 一般電腦科學
  • 一般材料科學
  • 一般工程

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