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A new image dehazing algorithm based on adaptive sky region is proposed in this paper, which shows good fidelity in sky region and satisfying visual effect in non‐sky region. For robust sky segmentation, we propose a rough‐to‐fine method that can make a balance between efficiency and accuracy. Considering distribution of haze is inconsistent, we divide the input image into three parts and calculate their atmospheric lights respectively. To solve the problem of invalid dark channel prior, we make an improvement for the transmission estimation. Finally, image fusion is taken as a post processing that can solve the problem of partial darkness and ensure a visual pleasing result. The experimental results for both synthetic and natural hazy images demonstrate that our algorithm performs comparable or even better results than the state‐of‐the‐art methods in terms of various measurement indexes, such as the PSNR, SSIM, and so forth. Besides, the proposed algorithm can be also applied in FPGA platform due to the optimized performance. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Facial micro‐expression recognition is a natural mechanism of facial behavior with subtle muscle movements and short duration, which is widely considered to be hard to recognize. In this paper, we propose the temporal sampling deformation (TSD) to normalize the temporal lengths and conserve time domain information for micro‐expression sequences. A three‐stream combining 2D and 3D convolutional neural network (TSNN) is also proposed to capture the features of micro‐expressions and classify the expressions as well. The proposed network has two variants TSNN‐IF and TSNN‐LF, which can automatically learn spatial and temporal features at the same time. Single domain experiments and cross‐domain experiments are also performed in the three benchmark datasets (chinese academy of sciences micro‐expression II (CASME II), spontaneous micro‐expression database (SMIC), and spontaneous micro‐facial movement dataset (SAMM)) to verify the effectiveness and validity of the proposed framework. Comprehensive results and ablation studies show that the proposed method can achieve comparable or even better results compared with other state‐of‐the‐art methods for micro‐expression recognition. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Chinese ink painting is a traditional art form that is highly regarded throughout the world for its theory, expression, technicality, and artistry. In this paper, we present a method to convert a photograph into a Chinese ink painting. First, the structure description map (SDM) for a photo is estimated to build the object appearance depiction. To make the converted Chinese painting's color be consistent with traditional color requirement of Chinese ink painting, a color transform algorithm is proposed to put color on the SDM. A qualitative evaluation approach is also proposed to carry out a comparative study with other simulation methods. Conversion results demonstrate that, using the proposed method, one can produce very beautiful Chinese ink painting from a photo with less user interaction and much faster conversion speed compared to other approaches. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]