自适应立方卷积图像插值算法

图像插值是图像处理的一项重要技术,可适用于多个领域,近年来多使用该技术进行图像缩放.针对传统图像缩放算法边缘处理效果较差、边缘检测插值算法复杂度高的问题,提出一种有效增强边缘轮廓的自适应立方卷积插值算法.该算法结合边缘梯度变化和立方卷积插值的特点,使得图像在平坦和纹理区域均能取得理想效果.实验结果表明,与基于边缘检测的插值算法相比,该算法具有较低的复杂度,平均运算时间降低了3.19 s;与立方卷积算法相比,图像峰值信噪比有较大的提高,峰值信噪比增加了0.89 dB.

Adaptive cubic convolution based image interpolation approach

Image interpolation is an important technique of image processing, which can be used in many image process areas. In recent years, it is often used to zoom in or zoom out images. A novel effective image interpolation mechanism to enhance the enlarged image edges was proposed for the visual artifacts problem in traditional magnification algorithms and the high computational cost in some adaptive image interpolation algorithms. The proposed algorithm combines the edge-directed gradient with the cubic convolution interpolation algorithm to obtain the higher quality of an image both in the edges and smooth areas. The result shows that the proposed algorithm gets a better visual effect and effectively removes the jaggy and blur at the edge. The proposed algorithm is less complex with running time reduced by 3.19 s on average, compared with the edge-adaptive interpolation algorithm, and has higher quality with the peak signal-to-noise ratio (PSNR) raised by 0.89 dB on average, compared with the cubic algorithm.