Optics and Precision Engineering, Volume. 30, Issue 10, 1246(2022)
Image dehazing method based on adaptive bi-channel priors
Fig. 1. Flow chart of adaptive bi-channel prior image dehazing method based on superpixel
Fig. 2. Haze-free images, bright channel images and histogram statistics of bright channel values
Fig. 3. Extract white or bright colors and black or dark pixels from hazy and haze-free images
Fig. 4. Extraction results of white or bright and black or dark pixels in fog-free images and composite foggy images
Fig. 5. Histogram statistics and cumulative distribution diagram of error
Fig. 6. Influence of soft matting filter on the dehazing result obtained by estimating the transmittance map based on a fixed-size rectangular area
Fig. 7. Haze-free image and images based on dark channel in different regions
Fig. 8. DCP, pixel-based DCP and superpixel-based BiCP method to obtain dehazing results
Fig. 9. Transmittance map and atmospheric light map based on super pixel BiCP dehazing method
Fig. 10. Atmospheric light, transmittance and dehazing results based on the superpixel BiCP and ABiCP methods
Fig. 11. DCP, pixel-based DCP, BiCP and ABiCP methods images dehazing results
Fig. 12. Example images of objective evaluation index of "BIT01" dehazing results obtained by various dehazing methods
Fig. 13. Quantitative comparison of dehazing results on the FRIDA dataset
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Yutong JIANG, Zhonglin YANG, Mengqi ZHU, Yi ZHANG, Lixia GUO. Image dehazing method based on adaptive bi-channel priors[J]. Optics and Precision Engineering, 2022, 30(10): 1246
Category: Information Sciences
Received: Jul. 8, 2021
Accepted: --
Published Online: Jun. 1, 2022
The Author Email: JIANG Yutong (jiangyutong201@163.com)