返回
Query by low-quality image
DOI:10.1016/j.imavis.2008.07.007.png)
摘要
En 中文
The motivation for research on low-quality images comes from a requirement by some museums to respond to queries for pictorial information, submitted in the form of fax messages or other low-quality monochrome images of works of art. The museums have databases of high-resolution images of their artefact collections and the person submitting the query is asking typically whether the museum holds the artwork shown or perhaps some similar work. Often the query image will have no associated meta-data and will be produced from a low-resolution picture of the original artwork. The resulting poor quality image, received by the museum, leads to very poor retrieval accuracy when the fax is used in standard query by example searches using, for example, colour, spatial colour or texture matching algorithms. We propose a special retrieval algorithm in order to improve the retrieval accuracy in query by low-quality image application and evaluate it in comparison with more conventional algorithms. Throughout this paper, fax images will be used as the main source of low-quality image for query by low-quality image experiments. Nonetheless, some other forms of low-quality image will also be considered. (C) 2008 Elsevier B.V. All rights reserved.
Keyword:
Content-based image retrieval
Low-quality image analysis
Wavelet transform
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.2
论文数:
4.1K
被引数:
6.7K
机构
引用论文
Longitudinal transcriptome analyses show robust T cell immunity during recovery from COVID-19纵向转录组分析显示新型冠状病毒肺炎恢复过程中T细胞免疫功能强大
Dynamic Changes in Myofibroblasts Affect the Carcinogenesis and Prognosis of Bladder Cancer Associated With Tumor Microenvironment Remodeling肌成纤维细胞的动态变化与肿瘤微环境重塑对膀胱癌发生及预后的影响

