可计算图像复杂度评价方法综述

doi:10.3969/j.issn.0372-2112.2020.04.024

电子学报 ›› 2020, Vol. 48 ›› Issue (4): 819-826.DOI: 10.3969/j.issn.0372-2112.2020.04.024

可计算图像复杂度评价方法综述

郭小英^1,3, 李文书², 钱宇华³, 白茹意¹, 贾春花¹

1. 山西大学软件学院, 山西太原 030013;
2. 浙江理工大学信息学院, 浙江杭州 310018;
3. 山西大学大数据科学与产业研究院, 山西大学计算智能与中文信息处理教育部重点实验室, 山西太原 030006

收稿日期:2019-01-16 修回日期:2019-05-27 出版日期:2020-04-25
- 作者简介:
- 郭小英 女,1985年1月出生于山西原平.2013年于日本广岛大学取得博士学位,现为山西大学软件学院副教授、硕士生导师,从事图像分析与视觉感知、情感计算、眼动追踪等研究.E-mail:guoxiaoying@sxu.edu.cn;李文书 男,1975年7月出生于黑龙江.于浙江大学取得博士学位,现为浙江理工大学信息学院教授、硕士生导师,主要研究方向为图像处理、认知建模.E-mail:charlie@zstu.edu.cn
- 基金资助:
- 国家自然科学基金 (No.61603228，No.31771224，No.61672332）; 国家科技部重点研发计划：重点专项课题 (No.2018YFB1004901）

Computational Evaluation Methods of Visual Complexity Perception for Images

GUO Xiao-ying^1,3, LI Wen-shu², QIAN Yu-hua³, BAI Ru-yi¹, JIA Chun-hua¹

1. School of Software Engineering, Shanxi University, Taiyuan, Shanxi 030013, China;
2. Department of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China;
3. Institute of Big Data Science and Industry, Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, Shanxi 030006, China

Received:2019-01-16 Revised:2019-05-27 Online:2020-04-25 Published:2020-04-25

摘要/Abstract

摘要： 可计算的图像复杂度评价是让计算机模拟人类视觉感知，从而对图像视觉复杂度进行决策的研究，该研究属于多学科交叉的创新性研究课题，在图像工程领域具有重要意义.本文针对可计算的图像复杂度评价方法进行了全面的梳理和分析，文中首先回顾了图像复杂度的应用领域，并详细阐述了图像复杂度评价方法，从信息论、图像压缩理论、图像特征分析、眼动数据等方面进行总结；随后，着重阐述基于图像特征的图像复杂度评价方法中所使用的图像特征；归纳图像复杂度建模中的分类和回归问题；最后，总结当前图像视觉复杂度评价方法存在的问题和挑战，展望图像复杂度的计算化发展方向.

关键词: 视觉复杂度, 情感感知, 复杂度评价, 特征提取, 分类与回归

Abstract: Modeling of image complexity is a research that builds a computer to sense the visual complexity of images in a way that is similar to the majority of people.The research is an interdisciplinary subject and is of great significance in the field of image engineering.In this article,the main methods of evaluating image complexity have been carried out by a comprehensive analysis.The paper reviews the different application fields of image complexity.Then the paper introduces the evaluation methods for visual complexity in detail from information theory,theory of image compression,image analysis and image modeling method of complexity.Especially,we focus on descriptions of the image features used in the complexity evaluation method based on the image features.In terms of image complexity assessment,we illustrate the classification and regression methods for evaluating complexity of images.This work also proposes the existing problems and challenges in the study of image complexity.

Key words: visual complexity, affective perception, complexity evaluations, feature extraction, classification and regression

中图分类号:

TP391

郭小英, 李文书, 钱宇华, 白茹意, 贾春花. 可计算图像复杂度评价方法综述[J]. 电子学报, 2020, 48(4): 819-826.

GUO Xiao-ying, LI Wen-shu, QIAN Yu-hua, BAI Ru-yi, JIA Chun-hua. Computational Evaluation Methods of Visual Complexity Perception for Images[J]. Acta Electronica Sinica, 2020, 48(4): 819-826.

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可计算图像复杂度评价方法综述

Computational Evaluation Methods of Visual Complexity Perception for Images

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