基于图像边缘保持的反距离加权插值算法

在数据可视化过程中运用一般的插值算法处理图像,边界效果通常比较模糊,也容易造成图像边缘信息的大量损失,导致图片整体增强效果欠佳。针对该问题,将图像边缘保持策略引入到反距离插值算法中,提出了基于图像边缘保持的自适应反距离加权插值算法(adaptive inverse distance weighted interpolation,AIDWI)。在图像边缘优化方向确定的基础上,利用反距离加权插值函数获取图像边缘区域像素间的关系,根据权值下降指数调节图像边缘的清晰度,设置平滑参数控制算法的平滑效应,达到图像整体增强效果的最佳状态。利用计算机进行图像增强仿真实验,通过基于图像能量谱的图像质量测度值和图像熵值对图像整体增强效果进行评估,结果表明经算法处理后的图像整体增强效果明显,算法在执行效率和提升图像熵值等方面均具有突出的优越性。

Adaptive inverse distance weighted interpolation algorithm based on image edge preserving

In the process of data visualization, the general interpolation algorithm is used to process the image, the boundary level is usually fuzzy, and it is easy to cause a large amount of loss of image edge information, which leads to the poor overall enhancement effect of the picture. In order to solve this problem, the image edge preserving strategy is introduced into the inverse distance interpolation algorithm, and an adaptive inverse distance weighted interpolation algorithm based on image edge preserving is proposed.. On the basis of establishing the optimization direction of the image edge, the relationship between pixels in the image edge region is obtained by using the inverse distance weighted interpolation function, according to the weight drop index, the definition of the image edge is adjusted, and the smoothing parameters are set to control the smoothing effect of the algorithm, so as to achieve the best state of the overall image enhancement effect. The computer simulation image enhancement experiment evaluates the overall image enhancement effect based on the image quality measurement value of image energy spectrum and image entropy. The results show that the overall image enhancement effect after the algorithm processing is obvious, and the algorithm has outstanding advantages in terms of execution efficiency and image entropy value promotion.