Multiscale Based Local Structurization Information Metric for Robust Pixel Level Image Fusion

YANG Zhi; MAO Shi-yi; CHEN Wei

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Multiscale Based Local Structurization Information Metric for Robust Pixel Level Image Fusion

机译：Multiscale Based Local Structurization Information Metric for Robust Pixel Level Image Fusion

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摘要

Because previous methods can not identify underlying image features from noises effectively, the updated image fusion schemes will be degraded when inputs are corrupted with noise. The perceptual salient image features often manifest some geometric structures, while noise dominated images are less structured. Based on complex wavelet transform, a structurization information metric is formulated by means of the Von Neumann entropy. The formulated metric can distinguish image features from noise very well. During the fusion process, the metric is employed to weight all fusion inputs. As a result, the perceptual meaningful inputs are enhanced while the noise inputs are de- emphasized adaptively. Comparing several image fusion schemes subjectively and objectively shows the good performance of the new scheme.

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来源
《Chinese Journal of Aeronautics》 |2005年第4期|352-358|共7页
作者
YANG Zhi; MAO Shi-yi; CHEN Wei;
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作者单位

School of Electronic Information Engineering, Beijing University of Aeronautics and Astronaut Beijing 100083, China;

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原文格式 PDF
正文语种英语
中图分类航空;
关键词
image fusion; dual-tree complex wavelet transform; Von Neumann entropy;

Multiscale Based Local Structurization Information Metric for Robust Pixel Level Image Fusion

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