CAJ | 학술논문

当前的各种TV(total variation)算法均只利用待修复点及其邻域的4个点的信息进行修复，由于所提供的参考信息有限，使得修复后的图像精确度欠佳。该文提出的双十字TV算法利用原始的TV算法，将待修复点邻域中的8个点分为两组，分别利用每组4个点的参考信息计算待修复点的像素值，然后将这两个像素值进行加权平均得到最终的修复值。实例验证结果表明，在不增加时间复杂度的情况下，双十字TV算法有效提高了修复后图像的精确度。
당전적각충TV(total variation)산법균지이용대수복점급기린역적4개점적신식진행수복，유우소제공적삼고신식유한，사득수복후적도상정학도흠가。해문제출적쌍십자TV산법이용원시적TV산법，장대수복점린역중적8개점분위량조，분별이용매조4개점적삼고신식계산대수복점적상소치，연후장저량개상소치진행가권평균득도최종적수복치。실례험증결과표명，재불증가시간복잡도적정황하，쌍십자TV산법유효제고료수복후도상적정학도。
The various total variation (TV) algorithms currently reconstruct the lost or deteriorated parts of images by related information of damaged pixel and its 4 neighborhood pixels. Their inpainting accuracy is low because of finite related information. The double cross TV algorithm proposed in this paper divides 8 neighborhood pixels into 2 groups, and computes the pixel value of damaged pixel by using 4 neighborhood pixels in each group respectively. Therefore, the weighted mean of these two pixel values is the final inpainting pixel value. The Experiments show an improvement in PSNR and less iteration number compared with the original TV.