计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
8期
131-135
,共5页
聚类分割%纹理合成%优先权%邻域灰度梯度差值
聚類分割%紋理閤成%優先權%鄰域灰度梯度差值
취류분할%문리합성%우선권%린역회도제도차치
clustering segmentation%texture synthesis%priority%neighborhood gray gradient difference
Criminisi提出的基于样本的图像修复技术需要在整幅图像中遍历样本,代价太大,并可能因选择错误的样本,不断迭代更新后而导致错误信息累积,使修复结果出现较大的偏差。同时,考虑到Criminisi算法中优先权函数的计算失误可能导致修复结果中出现结构失真,由此提出一种基于聚类分割和纹理合成的图像修复改进算法,将目标样本块的搜索限定在与源样本块所覆盖的类别一致的区域当中。在像素点优先权计算中,引入该像素点邻域灰度梯度差值信息,提出更为合理的优先权计算公式,以最大限度保证复杂场景中边缘优先传递,并在置信度更新项中有差别地对待新填充像素点。通过实验证明,改进算法不仅解决了Criminisi算法可能存在的结构偏差延续问题,修复视觉效果更加符合人们的主观感受,而且大大缩短了修复时间。
Criminisi提齣的基于樣本的圖像脩複技術需要在整幅圖像中遍歷樣本,代價太大,併可能因選擇錯誤的樣本,不斷迭代更新後而導緻錯誤信息纍積,使脩複結果齣現較大的偏差。同時,攷慮到Criminisi算法中優先權函數的計算失誤可能導緻脩複結果中齣現結構失真,由此提齣一種基于聚類分割和紋理閤成的圖像脩複改進算法,將目標樣本塊的搜索限定在與源樣本塊所覆蓋的類彆一緻的區域噹中。在像素點優先權計算中,引入該像素點鄰域灰度梯度差值信息,提齣更為閤理的優先權計算公式,以最大限度保證複雜場景中邊緣優先傳遞,併在置信度更新項中有差彆地對待新填充像素點。通過實驗證明,改進算法不僅解決瞭Criminisi算法可能存在的結構偏差延續問題,脩複視覺效果更加符閤人們的主觀感受,而且大大縮短瞭脩複時間。
Criminisi제출적기우양본적도상수복기술수요재정폭도상중편력양본,대개태대,병가능인선택착오적양본,불단질대경신후이도치착오신식루적,사수복결과출현교대적편차。동시,고필도Criminisi산법중우선권함수적계산실오가능도치수복결과중출현결구실진,유차제출일충기우취류분할화문리합성적도상수복개진산법,장목표양본괴적수색한정재여원양본괴소복개적유별일치적구역당중。재상소점우선권계산중,인입해상소점린역회도제도차치신식,제출경위합리적우선권계산공식,이최대한도보증복잡장경중변연우선전체,병재치신도경신항중유차별지대대신전충상소점。통과실험증명,개진산법불부해결료Criminisi산법가능존재적결구편차연속문제,수복시각효과경가부합인문적주관감수,이차대대축단료수복시간。
Criminisi proposed exemplar-based image inpainting techniques need to traverse the whole image exemplar, it is too costly, and may choose the wrong exemplar, constantly updates iteration error messages resulting cumulative, so that a greater deviation may be in inpainting results. Meanwhile, considering the Criminisi algorithm priority function cal-culation may lead to a structural distortion in inpainting results, which proposes an improved algorithm for image inpainting based on clustering segmentation and texture synthesis, the search will be limited to the same categories zone with the source exemplar covered. In the pixel priority calculation, the pixel neighborhood gray gradient difference information is introduced, the priority of more reasonable formula is proposed to ensure maximum edge preferentially transmitted in complex scenes and update entries in confidence difference to treat newly filled pixels. The experimental results show that the improved algorithm not only solves the Criminisi algorithm possible continuation of structural bias problem, repairing the visual effect is more in line with people’s subjective feelings, but also greatly shortens the repair time.