利用模拟退火技术对散焦图像进行深度恢复

K. Prasad, R. Mammone
{"title":"利用模拟退火技术对散焦图像进行深度恢复","authors":"K. Prasad, R. Mammone","doi":"10.1109/ICPR.1990.118099","DOIUrl":null,"url":null,"abstract":"The recovery of depth from defocused images is formulated as a 3-D image restoration problem. A defocused image is modeled as the combinatorial outcome of the depths and intensities of the volume elements (voxels) of an opaque 3-D object. A large depth-of-field image is used to constrain the intensities of the voxels. The depths of voxels are estimated from a highly defocused image by using simulated annealing to solve a constrained optimization problem. It is concluded that the method provides a framework for high-resolution depth recovery from defocused images. The method is computationally-intensive; however, it is amenable to parallel processing and is well suited for small field-of-interest applications.<<ETX>>","PeriodicalId":135937,"journal":{"name":"[1990] Proceedings. 10th International Conference on Pattern Recognition","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Depth restoration from defocused images using simulated annealing\",\"authors\":\"K. Prasad, R. Mammone\",\"doi\":\"10.1109/ICPR.1990.118099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recovery of depth from defocused images is formulated as a 3-D image restoration problem. A defocused image is modeled as the combinatorial outcome of the depths and intensities of the volume elements (voxels) of an opaque 3-D object. A large depth-of-field image is used to constrain the intensities of the voxels. The depths of voxels are estimated from a highly defocused image by using simulated annealing to solve a constrained optimization problem. It is concluded that the method provides a framework for high-resolution depth recovery from defocused images. The method is computationally-intensive; however, it is amenable to parallel processing and is well suited for small field-of-interest applications.<<ETX>>\",\"PeriodicalId\":135937,\"journal\":{\"name\":\"[1990] Proceedings. 10th International Conference on Pattern Recognition\",\"volume\":\"151 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1990] Proceedings. 10th International Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.1990.118099\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1990] Proceedings. 10th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.1990.118099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

从离焦图像中恢复深度被表述为三维图像恢复问题。散焦图像被建模为不透明三维物体的体素(体素)的深度和强度的组合结果。使用大景深图像来约束体素的强度。利用模拟退火算法对高度散焦图像进行体素深度估计,解决了约束优化问题。该方法为离焦图像的高分辨率深度恢复提供了一个框架。该方法计算量大;然而,它可以并行处理,非常适合小型领域的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Depth restoration from defocused images using simulated annealing
The recovery of depth from defocused images is formulated as a 3-D image restoration problem. A defocused image is modeled as the combinatorial outcome of the depths and intensities of the volume elements (voxels) of an opaque 3-D object. A large depth-of-field image is used to constrain the intensities of the voxels. The depths of voxels are estimated from a highly defocused image by using simulated annealing to solve a constrained optimization problem. It is concluded that the method provides a framework for high-resolution depth recovery from defocused images. The method is computationally-intensive; however, it is amenable to parallel processing and is well suited for small field-of-interest applications.<>
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信