Diffractive Optical Element (DOE) have emerged as a critical technology in modern optical systems, owing to their unique achromatic and thermal properties, et.al. These optical elements play a significant role in enhancing the image quality and athermalization of optical systems, particularly in applications such as infrared optical systems and high-end commercial instruments. Traditional methods for achieving athermalization, such as optical lens optimization, optical material matching, and wavefront encoding, often rely on the principles of optical focal length distribution and aberration theory, resulting in complex, heavy, and bulky optical systems. A hybrid optical system that combines DOE with traditional lenses offers a promising solution to mitigate the complexity and material dependence of athermalization. MLDOE, in particular, hold the potential to enhance diffraction efficiency over a broad range of wavelengths. However, MLDOE are highly susceptible to temperature fluctuations, which can degrade the imaging quality of hybrid optical systems. As a result, researchers have been exploring optimization designs for DOE in hybrid optical systems to ensure high diffraction efficiency across a wide temperature range and wide- or even multi- wavelength range.
In recent years, significant progress has been made in the field of DOE, thanks to modern advances in computational imaging technology. Several innovative techniques have been proposed to enhance the capabilities of DOE and address the challenges posed by athermalization such as full-spectrum imaging, coded DOE design, adaptive wiener filtering, learning-based designs, optical-digital joint design, chromatic aberration correction and image restoration. Despite the remarkable progress in single-layer DOE and computational imaging techniques, there has been a significant gap in research concerning the combination of optical system optimization design and blind deconvolution restoration algorithms for hybrid optical systems with MLDOE. This lack of exploration is especially evident in the context of athermalization requirements for hybrid optical systems. A method that unifies optical design and image restoration has the potential to mitigate the diffraction efficiency reduction caused by fluctuations in ambient temperatures and improve imaging quality under various conditions.
In a new study published in the Journal Optics Express by Associate Professor Shan Mao, Dr. Huaile Nie, and Professor Jianlin Zhao from the Northwestern Polytechnical University discussed the recent advancements in the field of DOE and their applications in athermalization, with a focus on a novel approach that combines optical system design with blind deconvolution restoration algorithms to achieve athermalization in hybrid optical systems with Multi-Layer DOE (MLDOE). They developed a new a method and highlighted its importance in achieving athermalization in hybrid imaging systems operating across wide temperature ranges.
To illustrate the potential of the proposed method, the authors presented a cooled dual-band infrared optical system with a Diffractive Layered DOE (DLDOE) for athermalization over a wide temperature range. The optical system design aims for simplicity, utilizing only two optical materials: germanium (Ge) and zinc selenide (ZnSe), with a limited number of lenses (five lenses). The system specifications include a focal length of 105 mm, an F-number of 1.5, and a full field of view of 6°. The next step involves the simulation of dual-band infrared images to evaluate the system’s performance under varying ambient temperatures. The authors developed a degradation model for image simulation based on the Bidirectional Inverse Aberration-Diffraction Efficiency (BIADE) of DLDOE, accounting for the influence of ambient temperature on image quality. The image simulation process comprises calculating BIADE for each diffraction order for both MWIR and LWIR at different temperatures and then applying these BIADE values to clear infrared images to simulate images at specific temperatures.
One important aspect of the new method is the restoration of the simulated images. This is achieved through the establishment of a Point Spread Function (PSF) for the dual-band infrared optical system at a working temperature of -20°C, which is used as an example. The PSF is computed for different diffraction orders, and a synthetic PSF is created to facilitate image restoration. Subsequently, the researchers employed a blind deconvolution algorithm for image restoration, without considering image noise. They showed the image quality is notably improved within the ambient temperature range, as confirmed by metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM).
In conclusion, the new study presented successfully a comprehensive digital-optical co-design approach offers a promising solution for achieving athermalization in refractive-diffractive hybrid imaging systems operating across a wide ambient temperature range. This approach addressed the challenges posed by MLDOE’ sensitivity to temperature variations and aims to enhance image quality and system efficiency. The study by Professor Shan Mao and colleagues presented a case study of a cooled dual-band refractive infrared hybrid optical system designed to achieve athermalization using only two common optical materials, Ge and ZnSe. Image simulation and restoration demonstrate the effectiveness of the proposed method in improving image quality over a broad temperature range. This approach not only enriches the application range of computational imaging technologies but also has the potential to streamline the design and reduce the cost of athermalization optical systems. As the field of optical engineering continues to advance, the integration of DOE and computational imaging offers exciting possibilities for the future of athermalization in optical systems.
Mao S, Nie H, Zhao J. Digital-optical co-design enables athermalization of hybrid optical systems. Opt Express. 2023 ;31(9):13837-13850. doi: 10.1364/OE.489326.