Depth and focused image recovery from defocused images for cameras operating in macro mode

Depth From Defocus (DFD) is a depth recovery method that needs only two defocused images recorded with different camera settings. In practice, this technique is found to have good accuracy for cameras operating in normal mode. In this paper, we present new algorithms to extend the DFD method to cameras working in macro mode used for very close objects in a distance range of 5 cm to 20 cm. We adopted a new lens position setting suitable for macro mode to avoid serious blurring. We also developed a new calibration algorithm to normalize magnification of images captured with different lens positions. In some range intervals with high error sensitivity, we used an additional image to reduce the error caused by drastic change of lens settings. After finding the object depth, we used the corresponding blur parameter for computing the focused image through image restoration, which is termed as "soft-focusing". Experimental results on a high-end digital camera show that the new algorithms significantly improve the accuracy of DFD in the macro mode. In terms of focusing accuracy, the RMS error is about 15 lens steps out of 1500 steps, which is around 1%.