Autofocusing technology is an essential automatic adjustment technology that relies on the clarity evaluation function to achieve clear and accurate imaging in imaging systems. This technology originated from traditional optical microscopes and has been widely promoted in the new generation of microscopic imaging systems, as well as in the more extensive application of computational microscopy imaging technology. Microscopic imaging is closely related to autofocusing technology, from the focusing process of the microscope stage to the calculation of distance parameters in computational imaging technology. Achieving fast and intelligent autofocusing performance in microscopic imaging systems is a pressing research task for the disciplines that apply computer vision automatic detection systems.

In this context, an autofocusing algorithm based on the Tanimoto coefficient was proposed to solve the problems of inaccuracy and low sensitivity of autofocusing results in colour microscopy due to complex colour changes. Background areas without useful information will result in a large amount of computation and affect the accuracy of autofocusing results. The Harris corner detection operator was used to extract the salient feature region as the definition evaluation object. In order to solve the contradiction between ergodic search and high-precision autofocusing in multi-range coherent diffraction imaging, a focusing algorithm based on subdivision search is proposed to accelerate the autofocusing process.