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An Adaptive Image Interpolation Method Focusing on Edge Information

机译:一种基于边缘信息的自适应图像插值方法

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In this paper, an adaptive interpolation method of digital image focusing on edge information is studied. The target is multi-level zoom ensuring image quality and keeping edge information. And this method is composed of three key models. (1) Accurate edge detecting model. Edge detecting model is the basic model to describe image features and the classic Canny edge detector is applied to get accurate image edge information. (2) Adaptive interpolation model. Kriging interpolation algorithm is used to interpolate zoom image using gray information and spatial distribution information of image. (3) adaptive image interpolation. Using Canny edge detector, original image is divided into edge and non edge region. And in image zoom process, the weighted neighborhood interpolation is applied to produce non edge pixels. Kriging interpolation is applied to produce edge pixels to Keep edge characteristics. Experiment is carried out to test the effectiveness and characteristics of this approach. Experimental results approve that it can realize multi-level zoom and keep edge information while image zoom out. Experimental results show the validity and practicability of the research method and it has good application potential.
机译:本文研究了一种基于边缘信息的数字图像自适应插值方法。目标是多级缩放,以确保图像质量并保留边缘信息。并且该方法由三个关键模型组成。 (1)精确的边缘检测模型。边缘检测模型是描述图像特征的基本模型,经典的Canny边缘检测器用于获取准确的图像边缘信息。 (2)自适应插值模型。克里格插值算法用于利用图像的灰度信息和空间分布信息对缩放图像进行插值。 (3)自适应图像插值。使用Canny边缘检测器,原始图像分为边缘区域和非边缘区域。并且在图像缩放过程中,将加权邻域内插应用于产生非边缘像素。应用克里格插值法来产生边缘像素以保持边缘特征。进行实验以测试这种方法的有效性和特征。实验结果表明,该方法可以实现多级缩放,并在缩小图像时保留边缘信息。实验结果证明了该方法的有效性和实用性,具有良好的应用潜力。

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