屏幕内容图像分割采用稀疏平滑分解

Shervin Minaee, AmirAli Abdolrashidi, Yao Wang
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引用次数: 35

摘要

稀疏分解已广泛应用于信号压缩降噪和文档分析等领域。本文将稀疏分解用于图像分割。该算法采用稀疏-平滑分解技术对背景和前景进行分离,使平滑分量和稀疏分量分别对应于背景和前景。该算法在HEVC测试序列的多个测试图像上进行了测试,结果表明该算法比DjVu中的分层k-means聚类等其他方法具有更好的性能。该分割算法还可用于文本提取、视频压缩和医学图像分割。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Screen content image segmentation using sparse-smooth decomposition
Sparse decomposition has been extensively used for different applications including signal compression and denoising and document analysis. In this paper, sparse decomposition is used for image segmentation. The proposed algorithm separates the background and foreground using a sparse-smooth decomposition technique such that the smooth and sparse components correspond to the background and foreground respectively. This algorithm is tested on several test images from HEVC test sequences and is shown to have superior performance over other methods, such as the hierarchical k-means clustering in DjVu. This segmentation algorithm can also be used for text extraction, video compression and medical image segmentation.
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