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Color image sharpening based on local color statistics

机译:基于局部颜色统计的彩色图像锐化

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This paper presents an effective color image sharpening method, which is based on local color statistics. First, the variance of a set of color samples is measured by a scalar that is computed based on the sum of distances of color vectors, whereas other studies usually treat a color variance as a 3D vector. This is because what a variance expresses is the degree of the deviation of the image (vector) signal from its mean, indicating that describing this degree of deviation by a scalar is reasonable. Then, the local scalar variance and mean vector are combined together to measure the change of color image signal from a pixel to its neighboring ones, and the polarity of the change is determined by the change of luminance. Finally, based on the measure of the change, an effective sharpening operator is developed. Experimental results show that the proposed method excellently sharpens different kinds of color images and at the same time preserves image chromaticity well, and outperforms other typical sharpening techniques in both objective assessment and visual evaluation.
机译:本文介绍了一种有效的彩色图像锐化方法,其基于局部颜色统计。首先,通过基于颜色矢量的距离之和计算的标量来测量一组颜色样本的方差,而其他研究通常通常将颜色差异视为3D矢量。这是因为方差表达的是图像(向量)信号与其平均值的偏差的程度,指示通过标量描述这种程度的偏差是合理的。然后,将局部标量纲和均值矢量组合在一起以测量从像素到其相邻的像素的变化,并且通过亮度的变化来确定变化的极性。最后,基于变化的衡量标准,开发了一种有效的锐化操作员。实验结果表明,该方法优良地锐化了不同种类的彩色图像,同时保留了图像色度良好,并且在客观评估和视觉评估中优于其他典型的锐化技术。

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