Over the past ten years, computational imaging has made significant advancements. The method combines cutting-edge hardware and algorithms to create photos that conventional cameras can’t catch. Researchers have created a revolutionary method called sparse holography that converts two-dimensional holograms into three-dimensional images using computational imaging techniques.
They created a set of algorithms and techniques to measure a two-dimensional hologram, then used those measurements to estimate three-dimensional objects. The generated image is a three-dimensional depiction of the scene rather than a snapshot. They claimed that a person could observe the 3D representation by 3D printing a model or utilizing interactive software. According to the researcher, the issue with imaging is that while cameras and imaging systems only produce two-dimensional images, the world is three-dimensional. The group’s main area of interest is how to take optical measurements as far as they can be made physically.
The sparse holography approach can be utilized when 3D images are required, notably when it’s necessary to make moving things appear three-dimensional. They say producing 3D photographs of moving things, such as live tissue or organisms seen under a microscope, is typically impossible. It’s possible because of the lack of holography.
Related Content: Fresnel Incoherent Correlation Holography