Generative adversarial network-based image super-resolution using perceptual content losses

09/13/2018
by   Manri Cheon, et al.
0

In this paper, we propose a deep generative adversarial network for super-resolution considering the trade-off between perception and distortion. Based on good performance of a recently developed model for super-resolution, i.e., deep residual network using enhanced upscale modules (EUSR), the proposed model is trained to improve perceptual performance with only slight increase of distortion. For this purpose, together with the conventional content loss, i.e., reconstruction loss such as L1 or L2, we consider additional losses in the training phase, which are the discrete cosine transform coefficients loss and differential content loss. These consider perceptual part in the content loss, i.e., consideration of proper high frequency components is helpful for the trade-off problem in super-resolution. The experimental results show that our proposed model has good performance for both perception and distortion, and is effective in perceptual super-resolution applications.

READ FULL TEXT

page 8

page 12

page 13

research
11/01/2018

Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network

Convolutional neural network (CNN) based methods have recently achieved ...
research
07/24/2019

Image Super-Resolution Using a Wavelet-based Generative Adversarial Network

In this paper, we consider the problem of super-resolution recons-tructi...
research
10/09/2019

Wavelet Domain Style Transfer for an Effective Perception-distortion Tradeoff in Single Image Super-Resolution

In single image super-resolution (SISR), given a low-resolution (LR) ima...
research
04/24/2019

Super-resolution based generative adversarial network using visual perceptual loss function

In recent years, perceptual-quality driven super-resolution methods show...
research
11/08/2019

Joint Demosaicing and Super-Resolution (JDSR): Network Design and Perceptual Optimization

Image demosaicing and super-resolution are two important tasks in color ...
research
06/09/2023

HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection

An individualised head-related transfer function (HRTF) is essential for...
research
09/17/2021

WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data

The transition to green energy grids depends on detailed wind and solar ...

Please sign up or login with your details

Forgot password? Click here to reset