A novel image edge smoothing method based on convolutional neural network

Hui-Hong Xu,Dong-Yuan Ge

doi:10.1177/1729881420921676

Abstract

In the field of visual perception, the edges of images tend to be rich in effective visual stimuli, which contribute to the neural network’s understanding of various scenes. Image smoothing is an image processing method used to highlight the wide area, low-frequency components, main part of the image or to suppress image noise and high-frequency interference components, which could make the image’s brightness smooth and gradual, reduce the abrupt gradient, and improve the image quality. At present, there are still problems such as easy blurring of the edges of the image, poor overall smoothing effect, obvious step effect, and lack of robustness to noise on image smoothing. Based on the convolutional neural network, this article proposes a method for edge detection and deep learning for image smoothing. The results show that the research method proposed in this article solves the problem of edge detection and information capture better, significantly improves the edge effect, and protects the effectiveness of edge information. At the same time, it reduces the signal-to-noise ratio of the smoothed image and greatly improves the effect of image smoothing.

Highlights

The image has rich and well-structured visual information, but it is often disturbed by noise during transmission and acquisition
This article is based on the application of convolutional neural network (CNN) and edge detection in image smoothing; deep learning of image processing is carried out by edge information detection and network feature fusion
The results show that the CNN proposed in this article solves the problem of edge detection and

Summary

Introduction

The image has rich and well-structured visual information, but it is often disturbed by noise during transmission and acquisition. Edge smoothing of images helps guide the computer to more accurately recover images, analyze and extract visual information in images more efficiently, and facilitate more advanced visual tasks. It is important to study the image edge smoothing as an image processing technology in the field of image processing. Image smoothing helps to eliminate various interference noises, so that the high-frequency components in the image fade and the contrast reduced, save the low-frequency components, and the image information is extracted and saved most efficiently for subsequent processing of the image. This article is based on the application of convolutional neural network (CNN) and edge detection in image smoothing; deep learning of image processing is carried out by edge information detection and network feature fusion.

Methods

Results

Conclusion