Optical sectioning in 3D interferenceless coded aperture correlation holography by projecting images onto complex space and computational reconstruction

Imaging thick and complex objects remains a significant challenge because out-of-focus information produces blurred background noise. Traditionally, especially in biological studies, physical sectioning has been the gold standard for depth-resolved imaging, but it irreversibly damages the sample. Confocal imaging offers a fully noninvasive alternative, enabling the acquisition of high-contrast 2D image stacks from 3D specimens with minimal background noise. However, current state-of-the-art confocal systems depend on pixel-by-pixel mechanical or electronic scanning, which substantially increases both imaging time and system cost. In this study, we introduce a new non-scanning optical sectioning and background noise suppression method based on the well-known technique of interferenceless coded aperture correlation holography. In the proposed method, three camera recordings are digitally projected onto the complex space; each camera recording is a system’s response to the appearance of a multi-plane object at the system’s input. The three camera recordings are different from each other since the object light is modulated by three different coded phase aperture masks. The image reconstruction is achieved through deconvolution between two complex-valued functions, the above mentioned system-to-object response and computational point spread function. The phase distribution of the deconvolution serves as a filter enabling reconstruction of images in the desired z-slice only, excluding out-of-focus images and minimizing background noise. The proposed method is verified through experimental validation with two and three depth planes. The experimental results are characterized by enhanced axial selectivity, reduced background noise, and high-quality reconstruction.