Target flow field reconstruction based on dual tree complex wavelet transform and optical flow

Background oriented system (BOS) technology is widely used for measuring flow field density information. The fingerprint information of high-speed target flow field can be calculated with the digital image correction (DIC) method. However, these traditional DIC algorithms are unable to obtain large-scale features of target flow fields and costing high computational complexity. To deal with those problems, a method combination of dual tree complex wavelet transform and optical flow (DTCWT-OF) is proposed. The proposed method adopts a much sparser gradient divergence regularization to obtain much more sparse statistical characteristics of the target flow field, and utilize the prior knowledge of the target flow field fingerprint information. Meanwhile, the reconstruction method is processed in the wavelet transform domain. Compared to traditional DIC methods, the experimental results show that the proposed method improves the SNR by 5dB and can achieve quasi real-time reconstruction.