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Human body region enhancement method based on Kinect infrared imaging

机译:基于kinect红外成像的人体区域增强方法

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摘要

To effectively improve the low contrast of human body region in the infrared images, a combing method of several enhancement methods is utilized to enhance the human body region. Firstly, for the infrared images acquired by Kinect, in order to improve the overall contrast of the infrared images, an Optimal Contrast-Tone Mapping (OCTM) method with multi-iterations is applied to balance the contrast of low-luminosity infrared images. Secondly, to enhance the human body region better, a Level Set algorithm is employed to improve the contour edges of human body region. Finally, to further improve the human body region in infrared images, Laplacian Pyramid decomposition is adopted to enhance the contour-improved human body region. Meanwhile, the background area without human body region is processed by bilateral filtering to improve the overall effect. With theoretical analysis and experimental verification, the results show that the proposed method could effectively enhance the human body region of such infrared images.
机译:为了有效地改善红外图像中人体区域的低对比度,利用几种增强方法的组合方法来增强人体区域。首先,对于Kinect采集的红外图像,为了提高红外图像的整体对比度,采用了具有多次迭代的最优对比度色调映射(OCTM)方法来平衡低亮度红外图像的对比度。其次,为了更好地增强人体区域,采用了Level Set算法来改善人体区域的轮廓边缘。最后,为了进一步改善红外图像中的人体区域,采用拉普拉斯金字塔分解来增强轮廓改善的人体区域。同时,通过双边滤波处理没有人体区域的背景区域,以提高整体效果。通过理论分析和实验验证,结果表明该方法可以有效地增强人体红外图像的区域。

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