Computer Simulation of Digital Holography Using Convolution Method

The convolution method serves as a computer simulation approach for digital holography implementation. In this technique, computers employ convolution algorithms to simulate light propagation and interference phenomena, thereby generating digital holographic images. Key advantages include high computational efficiency and satisfactory quality of produced holograms. From an implementation perspective, this typically involves discrete convolution operations using Fast Fourier Transform (FFT) algorithms to model wavefront propagation, where the impulse response function represents the free-space propagation kernel. The method demonstrates particular effectiveness in simulating Fresnel diffraction patterns through convolution with appropriate transfer functions. Additionally, the convolution method finds applications in related domains such as image processing (e.g., filtering operations) and signal processing (e.g., system response simulation). In practical code implementation, programmers often utilize optimized convolution functions from libraries like NumPy or MATLAB, ensuring proper sampling rates and padding techniques to avoid aliasing artifacts. Ultimately, the convolution method proves to be a highly valuable computational simulation technique with broad applicability across multiple scientific and engineering disciplines.