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Detecting Image Forgery in Single-Sensor Multispectral Images

机译:在单传感器多光谱图像中检测图像伪造

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With the advancements in digital technology, multispectral images have found use in fields like forensics, remote sensing due to their ability to perceive things which were otherwise non-existent. They are used to obtain more information about terrains, land cover and in forensics as certain things like blood stains are not visible in visible spectrum. But with newly developed photo-editing softwares, they can be easily manipulated without leaving any visible clue of manipulation, but will destroy the underlying correlation between different bands. Newly developed digital cameras employ a single sensor along with multispectral filter array (MSFA) and then interpolate the data at other locations, hence introducing a correlation between bands. In this paper, we have proposed an algorithm that can identify the lack of correlation at tampered locations in a multispectral image and can thus help in establishing the authenticity of the given multispectral image. We show the efficiency of our approach with respect to the size of tampered regions in images interpolated with one the most common demosaicking algorithm-binary tree-based edge sensing (BTES).
机译:随着数字技术的进步,多光谱图像已发现在等田地,如取证,遥感因其能够感知不存在的东西。它们用于获得有关地形,陆地覆盖和法医的更多信息,因为在可见光谱中不可见。但随着新开发的光编制软件,可以轻松地操纵它们而不留下任何可见的操纵线索,但会破坏不同频段之间的潜在相关性。新开发的数码相机采用单个传感器以及多光谱滤波器阵列(MSFA),然后在其他位置插入数据,从而在频带之间引入相关性。在本文中,我们提出了一种算法,其可以识别多光谱图像中的篡改位置处缺乏相关性,因此可以有助于建立给定多光谱图像的真实性。我们展示了我们对篡改区域的尺寸的方法的效率,其中图像中的图像中的图像中的一个是基于最常见的去迭代树的边缘感测(BTES)。

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