Computer-generated holography (CGH) is a technique that uses computers to generate holograms. The main principles of work for computer-generated holograms include the following:
Mathematical modelling: The hologram is generated by mathematically modelling the interference pattern formed by the interaction of light with the object being imaged.
Sampling: The hologram is sampled to convert the continuous interference pattern into a discrete representation that can be stored digitally.
Encoding: The discrete hologram is then encoded in a format that can be displayed or printed, such as a binary pattern on a spatial light modulator (SLM).
Reconstruction: The encoded hologram is then illuminated with a coherent light source, and the holographic image is reconstructed by the interference of the reference beam with the hologram.
Iterative refinement: The generated hologram may be refined through iterative techniques, such as iterative Fourier transform algorithms, to improve the quality of the reconstructed image.
The history of development
The history of computer-generated holograms (CGH) dates back to the 1960s when the first holographic image was created by Dennis Gabor, for which he was awarded the Nobel Prize in Physics in 1971. At that time, holography was a purely optical process which required the use of laser light to create interference patterns recorded on photographic film.
In the 1970s, researchers began exploring computers to generate holograms, which would allow for more complex and precise holographic images. The first computer-generated hologram was created in 1966 by Emmett Leith and Juris Upatnieks using an early digital computer.
Throughout the 1970s and 1980s, researchers continued to refine the process of computer-generated holography, using advances in computer technology to create more complex holographic images with greater resolution and accuracy.
In the 1990s and 2000s, computer-generated holography began to find practical applications, particularly in the field of security and anti-counterfeiting measures. CGH is now used in a variety of fields, including medical imaging, optical storage, and 3D printing.
Today, computer-generated holograms continue to be an active area of research, with new techniques and applications constantly being developed. With the increasing availability of powerful computer systems and advances in optics and laser technology, the use of CGH will likely continue to expand in the years to come.
Advantages of computer-generated holograms
Computer-generated holograms (CGHs) do not require a real object and that’s why offer several advantages over optical holograms:
- Flexibility: CGHs can be easily modified, reprogrammed and updated without the need to create a new physical hologram. This makes them ideal for a wide range of applications that require rapid prototyping and design changes.
- High resolution: CGHs can achieve very high resolution compared to optical holograms, which are limited by the size of the recording medium used. This makes them ideal for applications that require detailed and accurate 3D imaging.
- Reduced complexity: Optical holography requires a complex setup of lenses, mirrors, and lasers, whereas CGHs can be generated using a computer and a simple optical setup. This reduces the cost and complexity of holographic imaging systems.
- Durability: Optical holograms are typically fragile and can be easily damaged or degraded over time. CGHs, on the other hand, can be stored and replicated indefinitely without any loss of quality.
- Scalability: CGHs can be easily scaled up or down to meet the requirements of a particular application. This makes them suitable for a wide range of applications, from small-scale research projects to large-scale commercial products.
The benefits of CGHs make them a highly versatile and effective technology for a wide range of applications, from medical imaging and holographic displays to security and data storage.
