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In the end, an imaging system must provide a good image. But what do we mean by that? Most of the time, a good image still refers to photographic-quality images taken with a DSLR. However, if this standard is applied to images for soil monitoring, medical diagnostics, or autonomous driving, it could lead to over- or mis-specifications of the desired results.

Let’s see how imaging system architects and teams can use the image simulation features of the 草榴社区 Optical 草榴社区 portfolio to render and optimize the desired image from an imaging system.

Workflow and Results

As described in the following simplified example, simulating an image using CODE V, LightTools, and RSoft Photonic Device Tools is already possible. The example features an imaging system embedding a four-lens set and a CMOS sensor with 1.12 micron RGB pixels and a microlens array.

1. Simulate the image from the lens set optical properties using CODE V

The first step is to design the lens set and generate the corresponding PSF. We use the Image Simulation (IMS) feature in CODE V to simulate an image. Any 2D image can be imported into the tool. You then define the grid of PSFs to be computed over the object and the FFT grid size. You can add color, relative illumination parameters, and image sensor properties such as pixel size and the number of pixels. IMS will compute the convolution of the input image with the optical parameters defined and calculated by CODE V and will output the resulting image.

Image quality can then be assessed on the simulated image. Further optimization of the lens set can provide the desired image quality for the targeted application.

2. Simulate parasitic light with LightTools and RSoft Photonic Device Tools

Most imaging systems must be optimized further to avoid parasitic light and compromise the desired image quality. Ghost and flare are typical parasitic effects of imaging systems. You can use RSoft Photonic Device Tools and LightTools to predict ghost and flare in our simplified example of an imaging system. We want to predict parasitic light in the system because of sensor diffraction and reflection properties.A CMOS image sensor is usually a collection of micrometer size pixels that create a strong diffraction pattern. We must use RSoft Photonic Device Tools to get the optical properties of this surface. More specifically, DiffractMOD RCWA is an efficient tool for rigorously calculating transversely periodic device diffraction properties. It will output the reflection/transmission power for each diffraction order, the total reflection/transmission, the amplitude/phase/angle for each diffraction order, and the field distribution in the simulation domain. All results are stored in a BSDF file that can be exported to LightTools for further simulations. The third step is to import the lens set geometry from CODE V, add the sensor properties, import the BSDF files from RSoft, add a source (sun source in the following image) and use the ray path tool from LightTools to run Monte Carlo simulations to analyze all possible paths for parasitic light. The simulated result will resemble the image shown on the right.

Assessing the image with image quality metrics on simulated images enables further optimization of the system to achieve specifications suited to the targeted application. Virtual testing of simulated images through CODE V, LightTools, and RSoft Photonic Device Tools is a powerful workflow that avoids over-specifying an imaging system and saves time by anticipating the assembly and testing phase through simulations.