图像梯形退化校正的研究与实现

论文编号:TX402  论文字数:12616,页数:34

摘要

 图像几何失真校正是数字图像处理中的一个重要内容。对于存在着几何畸变和失真的图像进行检测和数据分析前，有必要消除这些失真。梯形失真的校正在现实运用中有较高的实用价值，例如遥感图像处理，车牌检测，模拟三维飞行模块。这些都已经在现实生活、训练中有了应用。本次毕业设计以Visual C++6.0为工作平台，通过编写程序来实现相应算法。处理过程预设了一副原图像，该图像通过退化算法得到当前图像的坐标点及灰度值，并返回该灰度值到预设图像相应的坐标点上，从而实现了图像的还原。在计算灰度值时采用了最近邻法和双线性插值法。验证了梯形退化和校正模型的正确性和可行性。通过实验分析，最近邻法的校正计算速度及复杂度上要优于双线性插值法，但是校正后图像质量还是双线性插值法好。
关键词：梯形失真；几何校正，坐标变换，灰度插值，双线性插值法
   
ABSTRACT

 Image geometric distortion correction is an important content of digital image processing. It is necessary for the image with geometric distortion and distortion to eliminate these distortions before being carried on detection and data analysis. The correction of the trapezoidal distortion has a higher practical value in the reality using, such as remote sensing image processing, license plate detection, 3D flight simulation module. These have applied in the real life and the training activities. The graduates design takes Visual C++6.0 as the working platform through the compiling procedure to achieve the corresponding algorithm. The treating processes have supposed an original map picture in advance. This picture can obtain the seat punctuation and the gray value of the current picture through the degenerated algorithm, and return to the gray value to the corresponding seat punctuation of the picture supposed in advance. Thus we can realize the picture return to original state. The procedure used the nearest neighbor and bilinear interpolation methods to compute gray value. It has confirmed accuracy and the feasibility of the trapezoid degeneration and the adjustment model. Through analyzing the test, we can know that the nearest neighbor method of correction calculation is faster and less complex than bilinear interpolation. But bilinear interpolation has batter quality than nearest neighbor method after the image having been corrected. 
 
Keywords : Trapezoidal distortion, Geometric Rectification， Coordinate Transformation，   Gray interpolation，   Bilinear interpolation

目录
摘要 I
ABSTRACT II
绪论 1
第一章 程序开发工具Microsoft Visual C++6.0 3
1.1  Visual C++ 6．0 简介 3
1.2  Visual C++ 6．0的特点 3
1.3  Visual C++ 6．0的开发环境 4
第二章 数字图像处理背景与数字化实现 6
2.1 数字图像处理背景 6
2.2 数字图像的数字化实现 7
第三章 几何畸变和几何校正 12
3.1 几何畸变产生原因 12
3.2 梯形畸变模型 13
3.5 几何畸变校正模型 14
3.2 空间坐标变换方法归纳 14
3.4 数字图像灰度插值 16
3.4.1 数字图像灰度插值的定义 16
3.4.2 最近邻插值法 17
3.4.3 双线性插值算法 18
3.4.4 三次立方卷积插值算法 19
3.4.5 三种校正方法的比较 21
第四章 程序实现和实验测试 22
4.1 灰度插值方法实现程序 22
4.2 程序实验测试 24
第五章 全文总结与展望 27
致谢 30
参考文献 31

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