Image Dehazing Algorithm Based on Multi-Scale Fusion and Adversarial Training

Yuhang Liu; Shuai Wu

doi:10.3788/LOP57.061015

[1] Tan R T. Visibility in bad weather from a single image. [C]∥2008 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2008, Anchorage, AK, USA. New York: IEEE, 10139948(2008).

[2] Berman D, Treibitz T, Avidan S. Non-local image dehazing. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 1674-1682(2016).

[3] He K M, Sun J, Tang X O. Single image haze removal using dark channel prior. [C]∥2009 IEEE Conference on Computer Vision and Pattern Recognition, June 20-25, 2009, Miami, FL, USA. New York: IEEE, 1956-1963(2009).

[4] Meng G F, Wang Y, Duan J Y et al. Efficient image dehazing with boundary constraint and contextual regularization. [C]∥2013 IEEE International Conference on Computer Vision, December 1-8, 2013, Sydney, NSW, Australia. New York: IEEE, 617-624(2013).

[5] Zhu Q S, Mai J M, Shao L. A fast single image haze removal algorithm using color attenuation prior[J]. IEEE Transactions on Image Processing, 24, 3522-3533(2015).

[6] Cai B L, Xu X M, Jia K et al. DehazeNet: an end-to-end system for single image haze removal[J]. IEEE Transactions on Image Processing, 25, 5187-5198(2016).

[7] Ren W Q, Liu S, Zhang H et al. Single image dehazing via multi-scale convolutional neural networks[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9906, 154-169(2016).

[8] Li B Y, Peng X L, Wang Z Y et al. AOD-Net: all-in-one dehazing network. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 4780-4788(2017).

[9] Ren W Q, Ma L, Zhang J W et al. Gated fusion network for single image dehazing. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 3253-3261(2018).

[10] Zhu H Y, Peng X, Chandrasekhar V et al. DehazeGAN: when image dehazing meets differential programming. [C]∥Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, July 13-19, 2018, Stockholm, Sweden. [S.l.: s.n.], 1234-1240(2018).

[11] Engin D, Genc A, Ekenel H K. Cycle-dehaze: enhanced CycleGAN for single image dehazing. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June 18-22, 2018, Salt Lake City, UT, USA. New York: IEEE, 938-946(2018).

[12] Li R D, Pan J S, Li Z C et al. Single image dehazing via conditional generative adversarial network. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 8202-8211(2018).

[13] Xu Y, Sun M S. Convolution neural network image defogging based on multi-feature fusion[J]. Laser & Optoelectronics Progress, 55, 031012(2018).

[14] Zhang Z H, Zhou W X. Image dehazing algorithm based on full convolution regression network[J]. Laser & Optoelectronics Progress, 56, 201003(2019).

[15] Zhao J T. Single-image defogging algorithm based on deep learning[J]. Laser & Optoelectronics Progress, 56, 111005(2019).

[16] Yang A P, Wang H X, Wang J B et al. Image dehazing based on transmission fusion and multi-guided filtering[J]. Acta Optica Sinica, 38, 1210001(2018).

[17] Liu K, Bi D Y, Wang S P et al. Single image dehazing based on sparse feature extraction[J]. Acta Optica Sinica, 38, 0310001(2018).

[18] McCartney E J. Optics of the atmosphere: scattering by molecules and particles[M]. New York: John Wiley and Sons, Inc.(1976).

[19] Li J C, Fang F M, Mei K F et al. Multi-scale residual network for image super-resolution[M]. ∥Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science. Cham: Springer, 11212, 527-542(2018).

[20] Yu F. -04-30)[2019-07-29]. https:∥arxiv.xilesou., top/abs/1511, 07122(2016).

[21] Zhang Y L, Tian Y P, Kong Y et al. Residual dense network for image super-resolution. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 2472-2481(2018).

[22] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 770-778(2016).

[23] Johnson J, Alahi A, Li F F. Perceptual losses for real-time style transfer and super-resolution[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9906, 694-711(2016).

[24] Russakovsky O, Deng J, Su H et al. ImageNet large scale visual recognition challenge[J]. International Journal of Computer Vision, 115, 211-252(2015).

[25] Simonyan K. -04-10)[2019-07-29]. https:∥arxiv.xilesou., top/abs/1409, 1556(2015).

[26] Li B Y, Ren W Q, Fu D P et al. Benchmarking single-image dehazing and beyond[J]. IEEE Transactions on Image Processing, 28, 492-505(2019).

[27] Tarel J P, Hautiere N. Fast visibility restoration from a single color or gray level image. [C]∥2009 IEEE 12th International Conference on Computer Vision, September 29-October 2, 2009, Kyoto, Japan. New York: IEEE, 2201-2208(2009).

[28] Chen C, Do M N, Wang J. Robust image and video dehazing with visual artifact suppression via gradient residual minimization[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9906, 576-591(2016).

[29] Liu L X, Liu B, Huang H et al. No-reference image quality assessment based on spatial and spectral entropies[J]. Signal Processing: Image Communication, 29, 856-863(2014).

[30] Saad M A, Bovik A C, Charrier C. Blind image quality assessment: a natural scene statistics approach in the DCT domain[J]. IEEE Transactions on Image Processing, 21, 3339-3352(2012).