1 research outputs found
Adaptive Densely Connected Super-Resolution Reconstruction
For a better performance in single image super-resolution(SISR), we present
an image super-resolution algorithm based on adaptive dense connection (ADCSR).
The algorithm is divided into two parts: BODY and SKIP. BODY improves the
utilization of convolution features through adaptive dense connections. Also,
we develop an adaptive sub-pixel reconstruction layer (AFSL) to reconstruct the
features of the BODY output. We pre-trained SKIP to make BODY focus on
high-frequency feature learning. The comparison of PSNR, SSIM, and visual
effects verify the superiority of our method to the state-of-the-art
algorithms