Feature Enhancement Using Gradient Salience on Thermal Image

Zelin Li, Jian Zhang, Qiang Wu, G. Geers
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引用次数: 11

Abstract

Feature enhancement in an image is to reinforce some exacted features so that it can be used for object classification and detection. As the thermal image is lack of texture and colorful information, the techniques for visual image feature enhancement is insufficient to apply to thermal images. In this paper, we propose a new gradient-based approach for feature enhancement in thermal image. We use the statistical properties of gradient of foreground object profiles, and formulate object features with gradient saliency. Empirical evaluation of the proposed approach shows significant performance improved on human contours which can be used for detection and classification.
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基于梯度显著性的热图像特征增强
特征增强是对图像中某些特定的特征进行强化,使其能够用于目标的分类和检测。由于热图像缺乏纹理和彩色信息,视觉图像特征增强技术不足以适用于热图像。本文提出了一种基于梯度的热图像特征增强方法。利用前景目标轮廓的梯度统计特性,构造具有梯度显著性的目标特征。经验评估表明,该方法在人体轮廓上的性能有了显著提高,可用于检测和分类。
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