.png){kind=icon}
返回
Gradient-based multiresolution image fusion
.png){kind=icon}
PRE
AI
DOI：10.1109/tip.2004.823821.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a fuse-then-decompose technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.
Keyword:
gradient image representation
image fusion
information fusion
multiresolution image processing
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:
13.7
论文数:
1.0W
被引数:
8.4W
机构
暂无机构信息
引用论文
分享收藏Fusion of visible and thermal imagery improves situational awareness可见光和热图像的融合提高了态势感知能力.png)
DISPLAYS
DISPLAYSIF3.4
PREAI
分享收藏Hydrogen Mobility Europe (H2ME): Vehicle and Hydrogen Refuelling Station Deployment Results欧洲氢能移动 (H2ME): 车辆和加氢站部署结果
OAAI
OAAI分享收藏A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application基于多尺度分解的图像融合方案的分类以及针对数码相机应用的性能研究PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
分享收藏
查看更多内容