Single-Frame Remote Sensing Image Super-Resolution Reconstruction Algorithm Based on Two-Dimensional Wavelet

The obtained precisely high frequency information is the key of single-frame image super-resolution reconstruction by using two-dimensional wavelet. Because the bicubic interpolation of high frequency components decomposed by wavelet will introduce noise, it will affect reconstruction effect. An improved algorithm using Fourier transform and zero-padding resampling instead of bicubic interpolation is proposed in this paper. The advantage of frequency domain interpolation is obtained by using Fourier transform and zero-padding resampling. And high frequency components obtained by wavelet decomposition of the original image can be interpolated optimally without introducing noise, which makes the high frequency details more precise in the reconstruction process. The experimental results show that the improved algorithm is superior to the traditional two-dimensional wavelet reconstruction algorithm, which can be applied to the single-frame remote sensing image super-resolution reconstruction.