基于网格线平移的图像显示适配算法

针对图像显示适配算法中会发生较多扭曲的问题,提出一个基于网格线平移(PTG)的图像显示适配算法。首先,通过Achantan方法计算图像重要度,提取出主体目标;其次,计算最优网格线位移,利用线移动不仅保持重要区域尺寸不变而且保护主体目标的纵横比例,双重约束可以避免扭曲;再次,使用下限和上限来抑制由于过度缩小和放大网格造成的失真;最后,为了达到更好效果,引入一个边缘网格舍弃过程,指派更宽空间到重要区域来减少畸变。利用图像重定向调查系统将PTG与重要度扩散列删除方法、重要度扩散线裁剪方法以及基于网格变形的方法进行比较,当图像中含有明显的主要目标时,PTG结果更优。实验结果表明,PTG的缩放结果具有更少扭曲,并在保留图像中的感兴趣区域和重要目标上明显优于对比算法。

Image retargeting algorithm based on parallel translation of gridlines

To resolve the problem that more distortions occured in image retargeting algorithm, an image retargeting algorithm based on the Parallel Translation of Gridlines (PTG) was put forward. Firstly, Achanta algorithm was used to compute the important degree and extract the main object. Secondly, the optimal grid line displacement was calculated. Using grid lines movement can keep the size of important areas and protect the aspect ratio of object and the dual constraints can avoid distortion. At the same time, the lower and upper thresholds were used to restrain the distortion caused by excessively narrowing and widening grids. Finally, in order to achieve better effect, a edge discarding process was introduced to assign wider space to the important area for reducing the distortion. Image retargeting survey system was used to compare PTG with the methods including column removal method with importance diffusion, seam carving method with importance diffusion and grid warping method, and PTG got a better result in images with obvious main goal. The experimental results show that PTG not only has less distortion but also retains the interest area and important object of the image than the comparison methods.