为了消除投影仪的伽马效应，近年来二值条纹投影轮廓术得到快速发展。如何确定合适的离焦量是二值条纹离焦投影三维测量的关键问题。离焦不足时，条纹会包含高阶谐波；离焦过度的话，条纹对比度降低，相位分辨率降低，同时噪声的影响相对变大。离焦不足或离焦过度都会影响相位测量精度。为了解决这一问题，基于数字相关法提出一种最优离焦量的确定方法。该方法利用条纹与其二阶微分的相关性来确定最佳离焦量，以获得准正弦条纹。在欠离焦和过离焦情况下，相关系数均较小，只有当条纹为准正弦条纹时，相关系数取得极大值。对该方法进行了数值模拟和实验验证。实验结果表明，所提方法具有速度快、准确性高的优点，可在二值条纹投影过程中实时跟踪相关系数并确定最佳离焦量。

基于三维数字图像相关（3D-DIC）方法，采用拼接技术对口腔印模的三维形貌进行了测量。针对具有复杂表面形貌的口腔印模，采用由四个水平布置的相机组成的两个3D-DIC 测量子系统，对每个子系统测量得到的局部形貌进行拼接，进而得到口腔印模的整体形貌。与传统的双相机3D-DIC 测量方法测量结果进行了比较。实验结果表明，采用本文方法能够较好地重构出复杂的口腔印模的三维形貌，为口腔印模的三维重建提供了一种新的途径，同时也为复杂表面物体的三维形貌测量提供了参考。

提出了基于单幅彩色条纹投影的不连续物体及动态三维形貌的测量方法。该方法利用计算机产生一幅正弦条纹图和两幅单一强度图分别通过红蓝绿三个通道合成为一幅彩色条纹图，由液晶投影仪投影到被测物体表面，彩色CCD采集变形条纹图并保存在计算机中。通过三色分离，同时获得正弦条纹图和反映表面反射率分布及背景信息图，通过图像除法运算及亚像素精度归一化处理实现物体三维形貌的恢复。对于表面形貌不连续的物体，利用蓝色分量的灰度图像进行二值化处理定位阴影或暗背景，从而引导正确的相位求解。实验验证了该方法对不连续物体动态测量方面的可行性。

针对数字全息中零级像的存在影响数字再现像的质量,分析数字全息图的记录、再现原理及频谱特性,提出了一种利用有限脉冲响应滤波器消除全息图数字再现中零级像的方法。该方法只需记录一幅数字全息图,不需要相移器材或其他辅助设备,直接利用数字图像处理对数字全息图在空域进行预处理,消除全息再现时的零级像干扰。对比了数字模拟和实验拍摄到的全息图在应用有限脉冲响应滤波器消除零级像前后的再现结果,表明该方法可消除零级衍射像,改善重建像质量,并且算法简单。

An effective method for reducing the speckle noise in digital holography is proposed in this paper. Different from the methods based on classical filtering technique, it utilizes the multiple holograms which are generated by rotating the illuminating light continuously. The intensity images reconstructed by a series of holograms generated by rotating the illuminating light possess different speckle patterns. Hence by properly averaging the reconstructed intensity fields, the speckle noises can be reduced greatly. Experimental results show that the proposed method is simple and effective to reduce speckle noise in digital holography.

An improved block-matching algorithm for fast motion estimation is proposed. The matching criterion is the sum of absolute difference. The basic idea is to obtain the best estimation of motion vectors by an optimization of the search process which can terminate the time-consuming computation of matching evaluation between the current block and the ineligible candidate block as early as possible and eliminate the search positions as many as possible in the search area. The performance of this algorithm is evaluated by theoretic analysis and compared with the full search algorithm (FSA). The simulation results demonstrate that the computation load of this algorithm is much less than that of FSA, and the motion vectors obtained by this algorithm are identical to those of FSA.