中文摘要：

目的 对于微距摄影来说,由于微距镜头的景深有限,往往很难通过单幅照片获得拍摄对象全幅清晰的图像.因此要想获取全幅清晰的照片,就需要拍摄多幅具有不同焦点的微距照片,并对其进行融合.方法 传统的微距照片融合方法一般都假定需要融合的图像是已经配准好的,也并没有考虑微距图像的自动采集.因此提出了一种用于微距摄影的多聚焦图像采集和融合系统,该系统由3个部分组成.第1部分是一种微距图像拍摄装置,该硬件能够以高精度的方式拍摄物体在不同焦距下的微距照片.第2部分是一个基于不变特征的图像配准组件,它可以对在多个焦点下拍摄的微距图像进行自动配准和对齐.第3部分是一个基于图像金字塔的多聚焦图像融合组件,这个组件能够对已经对齐的微距照片进行融合,使得合成的图像具有更大的景深.该组件对基于图像金字塔的融合方法进行了扩展,提出了一种基于滤波的权重计算策略.通过将该权重计算与图像金字塔相结合,得到了一种基于多分辨率的多聚焦图像融合方法.结果 论文使用设计的拍摄装置采集了多组实验数据,用以验证系统硬件设计和软件设计的正确性,并使用主观和客观的方法对提出的系统进行评价.从主观评价来看,系统合成的微距图像不仅具有足够的景深,而且在高分辨率下也能够清晰地呈现物体微小的细节.从客观评价来看,通过将系统合成的微距图像与其他方法合成的微距图像进行量化比较,在标准差、信息熵和平均梯度3种评价标准中都是最优的.结论 实验结果表明,该系统是灵活和高效的,不仅能够对多幅具有不同焦点的微距图像进行自动采集、配准和融合,并且在图像融合的质量方面也能和其他方法相媲美.

英文摘要：

Objective 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. Method Most multi-focus fusion algorithms assume that source ima- ges 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 fu- sion 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 previ- ously 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 muhiresolution can be obtained by combining weight calculation with canonical image pyramid. Result 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 ob