Obtaining an image that contains all relevant objects in focus is often made impossible by the limited depth of field of macro lens. Consequently

the obtained image will fail to be in focus for all objects

i.e.

if one object in the scene is in focus

another object will be out of focus. Macro images should be captured and fused with different degrees of focus to obtain a clear image for macro photography. Most multi-focus fusion algorithms assume that source images possess point-wise correspondence

i.e.

the colors at and around any given pixel in one image correspond to the colors at and around that same pixel in another image. However

when a mechanical device is used to capture different in-focus images

small motion inevitably occurs between adjacent images.This study proposes a multi-focus image capture and fusion system for macro photography. The system consists of three parts. The first component is a multi-focus image capture device that can capture a series of macro images with high precision. These images are taken at different focus distances from a photographic subject. The second component is a feature-based method that can automatically align multiple in-focus images. The third component is a multi-focus image fusion method that combines multiple images taken and aligned previously with a fused image with a large depth of field. The proposed fusion method is based on Gaussian and Laplacian pyramids with a novel weight map computation strategy.A multifocus image fusion method based on multiresolution can be obtained by combining weight calculation with canonical image pyramid. Several data sets are captured and tested with the use of the proposed system to verify the soundness of hardware and software design. Subjective and objective methods are also used to evaluate the proposed system. According to the subjective evaluation

the fused macro image generated by the system not only has sufficient depth of field but can also clearly present small details of the object at high resolution. According to the objective evaluation

the synthesized macro image of the system is optimal in all three types of evaluation criteria

namely

standard deviation

average gradient and information entropy when compared with those obtained with other methods. An analysis of the experimental results shows that this system is flexible and efficient.The system can acquire

register

and fuse multiple multi-focus macro photos with fused image quality that is comparable with that of other methods.