CAJ | 학술논문

针对流体运动图像计算(也称为PIV),为了获得可靠的运动矢量场、散度场和旋度场,该文提出了一种基于非线性滤波思想的PIV计算方法.新方法属于变分PIV方法,其在克服传统PIV方法不足的同时避开了经典变分方法中能量范函凸性和可微性的约束,将能量函数的最小化过程转变为非线性滤波过程.该文针对实际粒子图像序列与经典方法进行了实验和比较,结果证明新方法能够在有效抑制噪声的同时可以较好地保持在多流体运动的情况下运动矢量、散度和旋度场的细节信息.
침대류체운동도상계산(야칭위PIV),위료획득가고적운동시량장、산도장화선도장,해문제출료일충기우비선성려파사상적PIV계산방법.신방법속우변분PIV방법,기재극복전통PIV방법불족적동시피개료경전변분방법중능량범함철성화가미성적약속,장능량함수적최소화과정전변위비선성려파과정.해문침대실제입자도상서렬여경전방법진행료실험화비교,결과증명신방법능구재유효억제조성적동시가이교호지보지재다류체운동적정황하운동시량、산도화선도장적세절신식.
For fluid motion image computation (PIV), a nonlinear filtering based PIV approach was proposed which can obtain reliable motion vector, div and curl fileds. As variational based PIV approaches the new approach is a nonlinear filtering process instead of an energy minimizing process, which can overcome the shortage of correlation based PIV approaches and avoid the restrictions of convexity and differentiability required by classical variational approaches. Experimental results from real particle image sequences demonstrated that the new method can help to suppress the computation noise and increase the reliability of fluid motion characteristic and structural descriptions.