Adaptive Densely Connected Super-Resolution Reconstruction

12/17/2019
by   Tangxin Xie, et al.
38

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.

READ FULL TEXT

page 3

page 5

page 7

research
11/20/2019

Dual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution

Deep learning-based single image super-resolution enables very fast and ...
research
09/09/2019

LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-Resolution

In this paper, we develop a concise but efficient network architecture c...
research
07/18/2017

Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network

We propose a highly efficient and faster Single Image Super-Resolution (...
research
10/11/2018

Deep Bi-Dense Networks for Image Super-Resolution

This paper proposes Deep Bi-Dense Networks (DBDN) for single image super...
research
07/14/2022

E2FIF: Push the limit of Binarized Deep Imagery Super-resolution using End-to-end Full-precision Information Flow

Binary neural network (BNN) provides a promising solution to deploy para...
research
01/21/2021

GhostSR: Learning Ghost Features for Efficient Image Super-Resolution

Modern single image super-resolution (SISR) system based on convolutiona...
research
11/11/2020

Dense U-net for super-resolution with shuffle pooling layer

Single image super-resolution (SISR) in unconstrained environments is ch...

Please sign up or login with your details

Forgot password? Click here to reset