Computational holographic CGH

First, technical principles

The core of computational holography is to generate holograms that can modulate optical wavefront by computer algorithm. These holograms are reconstructed in an optical system to generate a user-defined wave front, which in turn forms the desired image or light field. In this process, the generation of hologram is the key, which determines the quality and accuracy of the final reconstructed image.

2. Inverse problem and solution method

Inverse problem:

In computational holography, solving a hologram from a given object-light wavefront intensity distribution is an inverse problem constrained by physical and hardware conditions.

The problem is pathological in nature, because a hologram that strictly satisfies all constraints and can reconstruct an artificially defined intensity distribution is not necessarily real.

Solution method:

Non-convex optimization algorithms: This class of algorithms is widely used to transform ill-conditioned inverse problems into optimal value solving problems. The accuracy of the solution depends on constraints, optimization framework and initialization conditions.

Constraint conditions include intensity distribution constraint of reconstructed wavefront, limited propagation bandwidth constraint, limited spatial scale constraint of hologram and unique intensity constraint of phase hologram.

Optimization framework: determines the search path for the optimal solution of the inverse problem. Commonly used optimization frameworks include alternate projection and gradient descent methods (such as stepwise descent and second-order gradient descent).

Initialization condition: In the non-convex optimization scenario of computational holography, it usually refers to the initial definition of the object's optical wavefront phase. The different phase of the initial compound light has a great influence on the final convergence point.

3. Application and progress

Applications:

Computational holography has a wide range of applications in virtual reality and augmented reality, head-up display, data encryption, laser processing and metasurface design.

Especially in the field of near-eye display, computational holographic technology provides the possibility to achieve high quality and high definition image display.

Progress:

In recent years, with the continuous improvement of optimization algorithms and the improvement of computer performance, the accuracy and efficiency of computational hologram reconstruction have been significantly improved.

Researchers are also exploring new hologram generation methods and optimization strategies to further expand the application range of computational holography and improve its performance.

Iv. Challenges and Future Prospects

Challenge:

Despite the remarkable progress in computational holography technology, there are still some challenges. For example, how to further improve the accuracy and efficiency of hologram reconstruction, and how to solve the speckle problem introduced by coherent light source.

Future outlook:

With the deepening of the cross-research between optics and computer science, it is believed that more innovative technologies and methods will be applied to the field of computational holography in the future.

These new technologies and methods will further promote the development of computational holography technology and make it play an important role in more fields.

To sum up, computational holography is a technology with broad application prospect and important research value. Through continuous exploration and innovation, it is believed that computational holographic technology will achieve breakthroughs and applications in more fields in the future.