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首页> 外文期刊>International journal of image and data fusion >Generation of enhanced information image using curvelet-transform-based image fusion for improving situation awareness of observer during surveillance
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Generation of enhanced information image using curvelet-transform-based image fusion for improving situation awareness of observer during surveillance

机译：使用基于曲线波变换的图像融合生成增强的信息图像，以提高观察者在监视过程中的态势感知

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摘要

Image fusion has been widely used to combine multispectral information into an enhanced information image. The application of such enhanced information content in the field of surveillance for improving situation awareness of observer is highly recommended. When a single sensor information is used for surveillance like visible camera output during poor ambient lighting conditions, 'hot-target' details are not visible to the observer. The use of visible-infrared fused image is recommended during surveillance in poor ambient lighting conditions to visualise background scene details and 'hot-target' details simultaneously. A wrapping-based curvelet transform method is proposed for fusion of infrared and visible images. Curvelet transform is used because of its advantages over wavelet transform limitations like directional insensitivity, isotropic basis and inability to resolve curves. The approximation coefficients are fused using the principal component analysis rule while detailed coefficients are fused using absolute maximum rule. The reconstructed fused image is compared with results of other fusion approaches proposed in literature. The performance of proposed wrapping-based curvelet fusion method is found visually and statistically better in comparison to other fused image outputs. The fused image obtained using proposed method retains background details as well as hot target presence with fidelity.
机译：图像融合已被广泛用于将多光谱信息组合成增强的信息图像。强烈建议在监视领域中使用此类增强的信息内容，以提高观察者的状况意识。当在恶劣的环境照明条件下使用单个传感器信息进行监视（例如可见的摄像机输出）时，观察者将看不到“热目标”细节。建议在恶劣的环境光照条件下进行监视时使用可见红外融合图像，以同时可视化背景场景细节和“热目标”细节。提出了一种基于包裹的Curvelet变换方法，用于红外和可见光图像的融合。之所以使用Curvelet变换，是因为其优于小波变换的局限性，例如方向不敏感，各向同性基础和无法解析曲线。使用主成分分析法则融合近似系数，而使用绝对最大法则融合详细系数。将重建的融合图像与文献中提出的其他融合方法的结果进行比较。与其他融合图像输出相比，在视觉和统计上都发现了建议的基于包装的Curvelet融合方法的性能。使用所提出的方法获得的融合图像保留背景细节以及保真度高的目标存在。

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