Fig. 1. Experimental setup

Fig. 2. DBC curves and the first derivative of DBC curves with different sampling numbers when the object is a double-slit. (a) 5000 samplings; (b) 2000 samplings

Fig. 3. Process of Seeded Region Growing

Fig. 4. Over-segmented image of object ‘5’ and diagram of windows expansion. (a) object image '5', the top right corner is the selected a priori background window; (b) Over-segmented image; (c) Diagram of windows expansion, where the shaded area is an incremental window (d）-（f) unifying the adaptive windows ; (g) table of parameters目标‘5’的过分割图像以及窗口扩展方式示意图。(a) 重构图像目标‘5’,右上角为选定的先验背景窗口；(b) 过分割的图像；(c)窗口扩展方式示意图,其中阴影部分为增量窗口 ；(d)-(f)统一窗口示意图；(g)参数示意图

Fig. 5. Searching processes of object’3’and object’4’; Adaptive windows in each iterations. (a), (c) Searching processes of object’3’and object’4’; (b), (d) Adaptive windows in each iterations

Fig. 6. The first derivative of DBC curves of object ‘3’and object’4’based on traditional fixed focus window and proposed adaptive windows with 5 000 samplings. (a) object’3’; (b) object’4’目标‘3’和目标‘4’在采样数 时传统固定对焦窗口算法和自适应对焦窗口算法的DBC离散一阶导数曲线。（a）目标‘3’；（b）目标‘4’

Fig. 7. The first derivative of DBC curves of object ‘3’and object’5’ based on traditional fixed focus window and proposed adaptive windows with 2 000 samplings. (a) object’3’；(b) object’5’目标‘3’和目标‘5’在采样数 时传统固定对焦窗口算法和自适应对焦窗口算法的DBC离散一阶导数曲线。（a）目标‘3’；（b）目标‘5’

Fig. 8. Verify the proposed method with low samplings. (a), (c) The images of objects reconstructed at their axial positions (reference images); (b), (d) images of objects reconstructed using the adaptive focusing windows.

Table 1. Comparison of DBC value at z =L/4，z=L/2，z=3L/4