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Peripheral Detail-based Edge Preserving Image Interpolation Scheme

机译:基于外设细节的边缘保持图像插值方案

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Interpolation is a common technique for predicting unknown data points within the range of discrete known data points. In image processing and analysis applications, image interpolation is employed for changing image resolution but also for tasks like image rotation and other transformations. Classical image interpolation algorithms such as nearest neighbour, bilinear and bicubic interpolation are simple and fast. However, due to the high distortion along image details such as edges, the resulting images are often low in quality. In order to reduce these distortions and preserve fine image details, we propose an edge preserving interpolation algorithm in this paper. Our proposed algorithm extracts and recognises the direction of edges in an image. Based on the extracted information about localisation of edges, interpolated pixels are either replicated or predicted from known neighbourhood pixels. Experimental results confirm our approach to give good image quality, outperforming various other interpolation algorithms.
机译:插值是用于预测离散已知数据点范围内的未知数据点的常用技术。在图像处理和分析应用中,采用图像插值来改变图像分辨率,而且用于改变图像旋转等任务和其他转换。经典图像插值算法,如最近的邻居,双线性和双向插值是简单且快速的。然而,由于沿着诸如边缘的图像细节的高畸变,所得到的图像通常很低。为了减少这些扭曲并保留细图像细节,我们提出了本文的边缘保留的插值算法。我们所提出的算法提取并识别图像中边缘的方向。基于关于边缘定位的提取信息,从已知的邻域像素复制或预测内插像素。实验结果证实了我们提供了良好的图像质量,优于各种其他插值算法的方法。

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