Optical Aberrations Correction in Postprocessing Using Imaging Simulation

As the popularity of mobile photography continues to grow, considerable effort is being invested in the reconstruction of degraded images. Due to the spatial variation in optical aberrations, which cannot be avoided during the lens design process, recent commercial cameras have shifted some of these correction tasks from optical design to postprocessing systems. However, without engaging with the optical parameters, these systems only achieve limited correction for aberrations. In this work, we propose a practical method for recovering the degradation caused by optical aberrations. Specifically, we establish an imaging simulation system based on our proposed optical point spread function model. Given the optical parameters of the camera, it generates the imaging results of these specific devices. To perform the restoration, we design a spatial-adaptive network model on synthetic data pairs generated by the imaging simulation system, eliminating the overhead of capturing training data by a large amount of shooting and registration. Moreover, we comprehensively evaluate the proposed method in simulations and experimentally with a customized digital-single-lens-reflex camera lens and HUAWEI HONOR 20, respectively. The experiments demonstrate that our solution successfully removes spatially variant blur and color dispersion. When compared with the state-of-the-art deblur methods, the proposed approach achieves better results with a lower computational overhead. Moreover, the reconstruction technique does not introduce artificial texture and is convenient to transfer to current commercial cameras. Project Page: https://github.com/TanGeeGo/ImagingSimulation .

Design and Simulation of an Ultra-Wide Field Optical Coherence Tomography Retinal Imaging System

Peripheral retinal imaging is a unique approach for assessing and monitoring ocular diseases. In this paper, we proposed a design for an optical coherence tomography system to accomplish ultrawide field (>120°) retinal imaging without montages. Scanning of the sample arm was achieved via two ellipsoidal mirrors. The optical design software Zemax and an eye model were used to estimate the inherent aberrations in the system and the optical performance of retinal imaging. Simulation results of the aberrations in the designed system indicated that the designed system can achieve an unprecedented imaging field of view (FOV) while maintaining acceptable resolution without sacrificing the working distance. This work suggests that ultrawide field optical coherence tomography retinal imaging is achievable, which is highly important for the diagnosis and treatment of ocular—especially peripheral—retinopathy.

The Mono/Bistatic SAR Imaging Simulation of Sea Surface with Breaking Waves Based on a Refined Facet Scattering Field Model

In order to analyze the scattering characteristics of sea surface under high sea state, a complete scattering model of sea surface considering breaking wave is established in this study based on the refined facet scattering field model (RFSFM) and the scattering theory of breaking wave. On the basis of this model, the influence of breaking waves on the mono/bistatic SAR imaging of sea surface at HH and VV polarization is studied. The results show that with the increase in wind speed, the coverage of breaking wave increases obviously and the consideration of breaking wave has a good correction for the scattering coefficient at HH polarization under grazing incidence; however, for VV polarization, the effect of breaking wave is very small.

Intelligent Recognition Method of Low-Altitude Squint Optical Ship Target Fused with Simulation Samples

To address the problem of intelligent recognition of optical ship targets under low-altitude squint detection, we propose an intelligent recognition method based on simulation samples. This method comprehensively considers geometric and spectral characteristics of ship targets and ocean background and performs full link modeling combined with the squint detection atmospheric transmission model. It also generates and expands squint multi-angle imaging simulation samples of ship targets in the visible light band using the expanded sample type to perform feature analysis and modification on SqueezeNet. Shallow and deeper features are combined to improve the accuracy of feature recognition. The experimental results demonstrate that using simulation samples to expand the training set can improve the performance of the traditional k-nearest neighbors algorithm and modified SqueezeNet. For the classification of specific ship target types, a mixed-scene dataset expanded with simulation samples was used for training. The classification accuracy of the modified SqueezeNet was 91.85%. These results verify the effectiveness of the proposed method.