Clear microscopic images of algae are the basis of accurate identification. However, the microscopic images of algae located outside the depth of field are blurred due to the limited depth of field of the high-power microscope. On the one hand, some algal cells are large or filamentous in morphology. For example, the length of Anabaena sp. can reach hundreds of microns, and the depth distance of the algal cells can easily exceed the depth of field range of the microscope during microscopic imaging, and thus the area outside the depth of field range in the microscopic image is blurred due to defocus. On the other hand, the length of algal species with small cell size such as Scenedesmus sp. is only about seven microns, and the depth distance between multiple algal cells in the same field can easily exceed the depth of field of the microscope, which results in blurred algal cells in the collected microscopic algal images. Therefore, it is of great value to collect multi-focus microscopic images of the same field at different heights of the objective table and use the multi-focus image fusion method to realize multi-focus image fusion of algal cell images, so as to obtain clear images with panoramic depth.

In this paper, the focus area, defocus area, and background area of the microscopic images of the algal cell are detected, and then the multi-focus microscopic images are fused by using a spatial domain image fusion method. First, Laplacian energy and guided filtering are used to measure the local focus degree of algal cell images, and the focus area of microscopic algal cell images is determined after binarization, as shown in Eq. 4. Because the area where the algal cell is located can be detected by the S channel of HSV color space of the microscopic algal cell image, the defocus area of the microscopic image can be detected by combining the S channel with the focus area. The remaining parts are defined as background areas. Then the multiple microscopic images are fused in the spatial domain (Eq. 8), or in other words, the output pixel value is selected from the focus area with a larger focus degree. The defocus area does not participate in the fusion, and the average value of the background area is taken as the fused output, so as to realize the spatial domain fusion of the multi-focus microscopic algal cell images.

One microscopic image of algal cells is acquired by moving the precision displacement objective table every 1 μm in the direction of the depth of field. Anabaena sp., Scenedesmus sp., and Pediastrum sp. are used as experimental objects. The multi-focus microscopic images of Anabaena sp., Scenedesmus sp., and Pediastrum sp. are continuously acquired by moving 7, 7, and 15 μm in the direction of the depth of field of the objective table, respectively. There are different clear areas and defocus areas in each microscopic image due to the limitation of the microscope's depth field. The fusion effects of the wavelet transform, Laplacian pyramid, and pulse coupled neural network (PCNN) methods are compared with the proposed method in terms of subjective vision and objective quantitative evaluation. It can be seen from Fig. 5 and Fig. 6 that the proposed method can better transfer the focus area in the source image to the fusion image in subjective vision and has a better fusion effect. In terms of objective quantitative evaluation, Table 1 shows the edge information retention, spatial frequency, and average gradient of the fused images of Anabaena sp. (0.3529, 8.9654, and 0.0055), Scenedesmus sp. (0.3778, 7.0558, and 0.0023), and Pediastrum sp. (0.2940, 1.5445, and 0.0005), respectively, which are better than those of the compared methods. The proposed method effectively fuses the multi-focus microscopic images of algae and provides a method for obtaining the microscopic images of algae with panoramic depth.

In order to solve the problem of image blurring caused by the defocus diffusion effect in obtaining microscopic algal cell images, a spatial-domain multi-focus image fusion method is proposed in this paper. Laplace energy and guided filtering are used to detect the focus area of microscopic images, and obvious color characteristics of algal cell images are used to detect the defocus area by combining the S channel of HSV color space with the focus area. Then, the output image is selected according to the focus degree of the focus area in the spatial domain image fusion process. The experimental results show that the proposed fusion method can effectively fuse multi-focus microscopic images of algal cells. The fused image has better clarity, and the edge information of the source image is more effectively transmitted to the fused image. This work proposes a new method for obtaining microscopic images of algal cells with panoramic depth and provides technical support for the development of automatic monitoring instruments for algal cells.