结合主成分分析和图像分块的重定向研究  

Retargeting method based on principal component analysis and image blocking

作　　者：彭晏飞[1] 王静 刘晓轩 巩胜杰 PENG Yanfei;WANG Jing;LIU Xiaoxuan;GONG Shengjie(School of Electronic and Information Engineering,Liaoning Technical University,Huludao 125105,China)

机构地区：[1]辽宁工程技术大学电子与信息工程学院,辽宁葫芦岛125105

出　　处：《液晶与显示》2024年第2期157-167,共11页Chinese Journal of Liquid Crystals and Displays

基　　金：国家自然科学基金(No.61772249);辽宁省高等学校基本科研项目(No.LJKZ0358);辽宁工程技术大学双一流学科创新团队资助项目(No.LNTU20TD-27)。

摘　　要：针对现有图像重定向方法视觉效果差和处理速度慢的问题,提出一种基于主成分分析法和分块的内容感知图像重定向方法。首先,利用主成分分析法融合梯度图和显著图来提取更加丰富的图像特征,避免主体信息失真;其次,相邻裁缝线由均值代替,避免像素不连贯;最后,根据能量图中列能量值的大小将图像分为显著区域和非显著区域,并行缩放分块,更加注重图像特征并提高运行效率。在MIT RetargetMe、DUT-OMRON和NJU2000数据集上进行实验分析,以主观感受和客观因子运行时间、SIFT-flow作为评价指标,与几种常用算法对比。实验结果表明,该方法保证了图像主体信息的完整性,平均运行时间为线裁剪算法的1/3。本文提出的方法不仅具有较优的视觉效果,而且可降低运算量。Aiming at the problem of poor visual effect and slow processing speed of existing image retargeting methods,a content-aware image retargeting method based on principal component analysis and blocking is proposed.First,the principal component analysis method is used to fuse the gradient map and the saliency map to extract more abundant image features to avoid the distortion of the main information.Then,the adjacent seams are replaced by the mean value to avoid pixel incoherence.Finally,according to the size of the column energy value in the energy map,the image is divided into salient regions and nonsalient regions,and the blocks are scaled in parallel to pay more attention to image features and improve operating efficiency.The experimental analysis is carried out on the MIT RetargetMe,DUT-OMRON and NJU2000 datasets,and the subjective perception,the objective factor running time and SIFT-flow are used as evaluation indicators to compare with several commonly used algorithms.The experimental results show that the method ensures the integrity of the image subject information,and the average running time is 1/3 of the seam carving algorithm.The proposed method not only has better visual effect,but also can reduce the computational complexity.

关 键 词：主成分分析法 能量图 分块 裁缝线 缩放 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]