基于边缘检测的数字媒体深度交互式图像分割算法  

Deep Interactive Image Segmentation Algorithm for Digital Media Based on Edge Detection

作　　者：何婧[1] 邱欣欣[1] 温强[1] HE Jing;QIU Xinxin;WEN Qiang(Film Academy,Modern College of Northwest University,Xi’an 710130,China)

机构地区：[1]西北大学现代学院电影学院,西安710130

出　　处：《吉林大学学报（信息科学版）》2024年第5期952-958,共7页Journal of Jilin University（Information Science Edition）

基　　金：2023年陕西省体育局常规课题基金资助项目(2023520)。

摘　　要：针对数字媒体深度交互式图像受噪声干扰,导致其边缘检测效果较差,影响其分割精度的问题,提出基于边缘检测的数字媒体深度交互式图像分割算法。首先,利用小波变换方法对数字媒体中的图像进行去噪处理,提高图像分割精度;其次,使用高斯函数与低通滤波增强去噪后的图像,提高图像的清晰度,为图像分割提供便利;最后,依据自适应阈值算法对数字媒体的图像进行边缘检测,像素合集中存在上下阈值。根据其上下阈值的计算求出像素合集中的高低两个阈值,并对其实施边缘连接,实现数字媒体图像分割。实验结果表明,所提方法对分割数字媒体图像去噪效果好,分割精度和效率高。Digital media deep interactive images are affected by noise,resulting in poor edge detection performance and affecting segmentation accuracy.Therefore,a digital media deep interactive image segmentation algorithm based on edge detection is proposed.Firstly,the wavelet transform method is used to denoise images in digital media to improve the accuracy of image segmentation.Secondly,Gaussian function and low-pass filter are used to enhance the denoised image,improve the image definition,and facilitate image segmentation.Finally,based on the adaptive threshold algorithm,edge detection is performed on digital media images.There are two thresholds in the pixel collection,the upper threshold and the lower threshold.The high and low thresholds in the pixel set are calculated based on the calculation of their upper and lower thresholds,and edge connections between the two thresholds are implemented to achieve digital media image segmentation.The experimental results show that the proposed method has good denoising effect,high segmentation accuracy,and high segmentation efficiency for segmented digital media images.

关 键 词：数字媒体 边缘检测 深度交互式图像分割算法 小波变换方法 MSRCR-HIS算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]