HIFI-Net: A Novel Network for Enhancement to Underwater Images

06/06/2022
by   Jiajia Zhou, et al.
0

A novel network for enhancement to underwater images is proposed in this paper. It contains a Reinforcement Fusion Module for Haar wavelet images (RFM-Haar) based on Reinforcement Fusion Unit (RFU), which is used to fuse an original image and some important information within it. Fusion is achieved for better enhancement. As this network make "Haar Images into Fusion Images", it is called HIFI-Net. The experimental results show the proposed HIFI-Net performs best among many state-of-the-art methods on three datasets at three normal metrics and a new metric.

READ FULL TEXT

page 2

page 6

research
05/01/2022

Reinforced Swin-Convs Transformer for Underwater Image Enhancement

Underwater Image Enhancement (UIE) technology aims to tackle the challen...
research
06/17/2019

A Fusion Adversarial Network for Underwater Image Enhancement

Underwater image enhancement algorithms have attracted much attention in...
research
08/29/2018

Fractional Multiscale Fusion-based De-hazing

This report presents the results of a proposed multi-scale fusion-based ...
research
02/17/2022

A Wavelet-based Dual-stream Network for Underwater Image Enhancement

We present a wavelet-based dual-stream network that addresses color cast...
research
05/28/2020

L^2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion

Images captured underwater often suffer from suboptimal illumination set...
research
09/08/2023

Toward Sufficient Spatial-Frequency Interaction for Gradient-aware Underwater Image Enhancement

Underwater images suffer from complex and diverse degradation, which ine...
research
05/25/2022

Image Colorization using U-Net with Skip Connections and Fusion Layer on Landscape Images

We present a novel technique to automatically colorize grayscale images ...

Please sign up or login with your details

Forgot password? Click here to reset