Kau Lih-Jen, Lee Tien-Lin
Department of Electronic Engineering & Graduate Institute of Computer and Communication Engineering, National Taipei University of Technology, No. 1 Section 3, Chung-Hsiao E. Road, Taipei 10608, Taiwan.
ScientificWorldJournal. 2013 Nov 18;2013:105945. doi: 10.1155/2013/105945. eCollection 2013.
An efficient approach to the sharpening of color images is proposed in this paper. For this, the image to be sharpened is first transformed to the HSV color model, and then only the channel of Value will be used for the process of sharpening while the other channels are left unchanged. We then apply a proposed edge detector and low-pass filter to the channel of Value to pick out pixels around boundaries. After that, those pixels detected as around edges or boundaries are adjusted so that the boundary can be sharpened, and those nonedge pixels are kept unaltered. The increment or decrement magnitude that is to be added to those edge pixels is determined in an adaptive manner based on global statistics of the image and local statistics of the pixel to be sharpened. With the proposed approach, the discontinuities can be highlighted while most of the original information contained in the image can be retained. Finally, the adjusted channel of Value and that of Hue and Saturation will be integrated to get the sharpened color image. Extensive experiments on natural images will be given in this paper to highlight the effectiveness and efficiency of the proposed approach.
本文提出了一种有效的彩色图像锐化方法。为此,首先将待锐化的图像转换到HSV颜色模型,然后仅对明度通道进行锐化处理,而其他通道保持不变。接着,我们将一种提出的边缘检测器和低通滤波器应用于明度通道以挑选出边界周围的像素。之后,对检测为边缘或边界周围的那些像素进行调整以锐化边界,而那些非边缘像素保持不变。基于图像的全局统计和待锐化像素的局部统计,以自适应方式确定要添加到那些边缘像素上的增量或减量幅度。通过所提出的方法,可以突出不连续性,同时保留图像中包含的大部分原始信息。最后,将调整后的明度通道与色相和饱和度通道进行整合,以获得锐化后的彩色图像。本文将给出关于自然图像的大量实验,以突出所提出方法的有效性和效率。