The study of super-resolution reconstruction based on visual attention and wavelet analysis

The super-resolution reconstruction is an important method for improving the image quality, which possesses widely application in the fields of video monitoring, remote sensing imaging, medical image processing, etc. In this paper, firstly, the salient edges and the boundaries of salient objects were obtained by using the salient characteristics of visual attention based on computer visual model and wavelet analysis; secondly, the super-resolution image was synthetically acquired by adopting the bilinear interpolation in the contour´s internal region and the adaptive interpolation in the boundaries´ external region respectively. The simulation results showed that the visual effect of the reconstructed model was more according with human visual characteristics. In addition, the subjective judgment and objective evaluation is better than traditional reconstruction algorithm. The algorithm in this paper achieves good effects and reaches good feasibility and validity.