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Natural Object/Artifact Image Classification Based on Line Features

机译:基于线特征的自然物/伪像图像分类

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摘要

Three features for image classification into natural objects and artifacts are investigated. They are 'line length ratio', 'line direction distribution,' and 'edge coverage'. Among the three, the feature 'line length ratio' shows superior classification accuracy (above 90%) that exceeds the performance of conventional features, according to experimental results in application to digital camera images. As the development of this feature was motivated by the fact that the edge sharpening magnitude in image-quality improvement must be controlled based on the image content, this classification algorithm should be especially suitable for the image-quality improvement applications.
机译:研究了将图像分类为自然物体和伪影的三个特征。它们是“线长比”,“线方向分布”和“边缘覆盖率”。根据应用于数码相机图像的实验结果,在这三个特征中,特征“线长比”显示出优越的分类精度(超过90%),超过了传统特征的性能。由于必须基于图像内容来控制图像质量改善中的边缘锐化幅度,因此推动了此功能的发展,因此该分类算法应特别适合于图像质量改善应用。

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