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摘要：随着图像处理技术的广泛应用，图像作为信息载体在日常生活中充当着越来越重要的角色，越来越多的领域需要用到高分辨率图像。但由于硬件性能的限制，照片往往达不到所需的分辨率，而硬件的改进要付出昂贵的代价，采用图像插值技术来提高图像的分辨率和清晰度，从软件方面进行改进具有十分重要的实用价值。对于网络传输的图像，由于网络带宽的限制，无法以满足需求的速度传输高分辨率图像。这时，利用低分辨率的图像应用插值方法得到高分辨率图像就成为人们追求的目标。24526
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本文主要考虑插值在图像缩放中的应用。首先介绍了三种经典的图像插值算法——最近邻域法、双线性插值法和双三次插值法，实现了上述算法，并简要阐述其优缺点；其次为了解决图像放大过程中边缘模糊及运算量大的问题, 采用一种基于细化后的图像边缘进行插值处理的图像放大方法. 首先对初步提取出的边缘进行细化, 获取边缘的较准确位置; 然后根据被插值点邻域内边缘点和非边缘点的数量和位置关系进行不同的插值处理. 实验表明该方法得到的放大图像有较好的视觉效果, 无明显锯齿现象, 且处理算法简单, 易于实现。
毕业论文关键字：图像放大; 图像插值; 边缘细化; 边缘插值
Application of the Interpolation in Improving the Resolution of the Image
Abstract: With the wide application of image processing technology, image as a carrier of information in our daily life plays a more and more important role. High resolution image is needed in more and more fields. But because of limited hardware performance, photos are often not up to the desired resolution and hardware improvements will have to pay a very high price, using image interpolation techniques to improve the image resolution and definition, improvement from the software side has a very important practical value. High resolution image also can not been transmitted directly in net because of limitation of net band broad．So，valid method for image interpolation has become the aim which people are pursuing.
In this paper, we consider the interpolation in the image scaling. First introduced three classic image interpolation algorithm - nearest neighbor, bilinear interpolation and bicubic interpolation method to achieve the above algorithm, and briefly describes the advantages and disadvantages .Then a method for image zooming based on thinned edge was proposed this paper. Firstly, thinning the preliminarily edge that was distilled to get the exact location of the edge, give the edge pixel and non- edge pixel different marks; then according to the edge point and non-edge point quantity and the position relations around the interpolation pixel take different interpolation processing . The experiment proved this method obtains the image that has fine visual effect, after enlargement the image edge is clear, without obvious denticle phenomenon. The processing algorithm is simple and easy torealize.
Keywords: Image scaling; Image interpolation; Edge thinning; Interpolation of edge
目录
1． 绪论 5
1.1 研究背景和研究现状 5
1.2 课题研究的目的和意义 6
1.3 应用领域 6
1.4 图像插值技术及方法概述 7
1.5 研究内容 8
1.6 论文结构 8
2． 传统的图像插值算法 9
2.1 问题的定义 9
2.2 最近邻域法 9
2.3 双线性插值法 11
2.4 双三次插值法 15
2.5其他算法简介 18
2.6实验结果与分析 18
3． 一种基于细化边缘的图像放大方法的实现 19