Image and video dehazing by regularized optimization

Images and videos captured in hazy weather often yield low contrast and offer limited visibility due to the presence of haze in the atmosphere. Dr Jiaxi studied the image and video dehazing problem. A novel and systematic regularized optimization method for the image and video dehazing problem was proposed. By employing the wavelet transform technique, the proposed regularized optimization algorithms for dehazing can be efficiently implemented and executed to provide fast and high quality image dehazing. Computational experiments have demonstrated the advantages of the proposed algorithm in haze removal and image reconstruction as well as in computational efficiency.