Design of Adaptive Video Image Dehazing Algorithm and FPGA Accelerated Implementation

Yongming TANG; Rongshi DAI; Feng YU; Tianpeng WANG

doi:10.11999/JEIT200554

Volume 43 Issue 9

Sep. 2021

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Yongming TANG, Rongshi DAI, Feng YU, Tianpeng WANG. Design of Adaptive Video Image Dehazing Algorithm and FPGA Accelerated Implementation[J]. Journal of Electronics & Information Technology, 2021, 43(9): 2542-2551. doi: 10.11999/JEIT200554

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Yongming TANG, Rongshi DAI, Feng YU, Tianpeng WANG. Design of Adaptive Video Image Dehazing Algorithm and FPGA Accelerated Implementation[J]. Journal of Electronics & Information Technology, 2021, 43(9): 2542-2551. doi: 10.11999/JEIT200554

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Design of Adaptive Video Image Dehazing Algorithm and FPGA Accelerated Implementation

doi: 10.11999/JEIT200554 cstr: 32379.14.JEIT200554

1.
School of Electronic Science & Engineering, Southeast University, Nanjing 210096, China
2.
Science and Technology on Electro-optic Control Laboratory, Luoyang 471009, China

Funds: Aeronautical Science Foundation of China (20155169017)

Received Date: 2020-07-06
Rev Recd Date: 2021-06-21

Available Online: 2021-08-09

Publish Date: 2021-09-16

Abstract

Abstract

This paper proposes an adaptive image dehazing algorithm, which fully considers the image features in different complex scenes and establishes an adaptive mechanism of the algorithm. The mechanism includes adaptive adjustments to whether the image is foggy, whether it is a sky area, or filter size, etc., which solves the bad effect that the traditional algorithm may cause when dehazing the depth mutation region. This article also implements FPGA acceleration for the adaptive image dehazing algorithm. Experimental results show that the algorithm can meet the real-time requirements of 1080P@60Hz video dehazing on XC7K325T FPGA video processing platform. For most light fog or heavy fog scenes, the image color of this algorithm is naturally free of oversaturation after dehazing. The average global contrast and saturation enhancement ratio are 0.309 and 0.994, which has obvious advantages compared with other dehazing algorithms in the field.
- Video dehaze,
- Adaptive mechanism,
- Real-time dehaze,
- Implementation on FPGA

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References(16)

References

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