基于图像质量评估的多传感器单色视频融合

M. P. Kumar, P. R. Kumar
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引用次数: 0

摘要

对图像融合(结合两种或多种模式的图像,如红外和可见光辐射)的兴趣日益增加,导致需要准确和可靠的图像评估方法。本文提出了一种新的方法,将来自同一场景的多个视频的信息内容进行合并,从而得到一个包含来自不同源视频的最优信息的合并视频。这个过程被称为视频融合,它有助于提供比源图像更高质量的图像(“质量”一词包含对特定应用的测量)。在这种技术中,不同的传感器(其冗余信息可以减少)用于各种相机,这些相机对于捕获所需的图像是必不可少的,也有助于减少。本文采用基于多分辨率奇异值分解(MSVD)的图像融合技术。MSVD的图像融合效果与小波融合效果相似。MSVD的思想是用奇异值分解(SVD)代替小波变换中的FIR滤波器。它在计算上非常简单,非常适合于遥感和天文学等实时应用。
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A multi sensor monochrome video fusion using Image Quality Assessment
The increasing interest in image fusion (combining images of two or more modalities such as infrared and visible light radiation) has led to a need for accurate and reliable image assessment methods. This paper gives a novel approach of merging the information content from several videos taken from the same scene in order to rack up a combined video that contains the finest information coming from different source videos. This process is known as video fusion which helps in providing superior quality (The term quality, connote measurement on the particular application.) image than the source images. In this technique different sensors (whose redundant information can be reduced) are used for various cameras that are imperative for capturing the required images and also help in reducing. In this paper Image fusion technique based on multi-resolution singular value decomposition (MSVD) has been used. The image fusion by MSVD is almost similar to that of wavelets. The idea behind MSVD is to replace the FIR filters in wavelet transform with singular value decomposition (SVD). It is computationally very simple and is well suited for real time applications like in remote sensing and in astronomy.
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