TY - JOUR
T1 - VLSI Implementation for an Adaptive Haze Removal Method
AU - Kuo, Yao Tsung
AU - Chen, Wei Ting
AU - Chen, Pei Yin
AU - Li, Cheng Hsien
N1 - Funding Information:
This work was supported in part by the Ministry of Science and Technology, Taiwan, under Grant MOST 105-2221-E-006-157-MY3.
Publisher Copyright:
© 2013 IEEE.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
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U2 - 10.1109/ACCESS.2019.2953959
DO - 10.1109/ACCESS.2019.2953959
M3 - Article
AN - SCOPUS:85078406530
SN - 2169-3536
VL - 7
SP - 173977
EP - 173988
JO - IEEE Access
JF - IEEE Access
M1 - 8903266
ER -