Autonomous driving vehicles have strong path planning and obstacle avoidance capabilities, which provide great support to avoid traffic accidents. Autonomous driving has become a research hotspot worldwide. Depth estimation is a key technology in autonomous driving as it provides an important basis for accurately detecting traffic objects and avoiding collisions in advance. However, the current difficulties in depth estimation include insufficient estimation accuracy, difficulty in acquiring depth information using monocular vision, and an important challenge of fusing multiple sensors for depth estimation. To enhance depth estimation performance in complex traffic environments, this study proposes a depth estimation method in which point clouds and images obtained from MMwave radar and cameras are fused. Firstly, a residual network is established to extract the multi-scale features of the MMwave radar point clouds and the corresponding image obtained simultaneously from the same location. Correlations between the radar points and the image are established by fusing the extracted multi-scale features. A semi-dense depth estimation is achieved by assigning the depth value of the radar point to the most relevant image region. Secondly, a bidirectional feature fusion structure with additional fusion branches is designed to enhance the richness of the feature information. The information loss during the feature fusion process is reduced, and the robustness of the model is enhanced. Finally, parallel channel and position attention mechanisms are used to enhance the feature representation of the key areas in the fused feature map, the interference of irrelevant areas is suppressed, and the depth estimation accuracy is enhanced. The experimental results on the public dataset nuScenes show that, compared with the baseline model, the proposed method reduces the average absolute error (MAE) by 4.7–6.3% and the root mean square error (RMSE) by 4.2–5.2%.

Optical information encryption technology has received extensive attention from researchers in recent years because of its advantages of parallel and high-speed processing capability, as well as the controllability of phase components. An encryption method for grayscale images with a pair of random phase masks based on gamma distribution in the gyrator domain is proposed. In this scheme, two random distribution phase-images using random parameters according to the definition of the gamma probability distribution function are generated. They are loaded onto spatial light modulators as random phase masks used in the encryption process. The input grayscale image transmitted through the first random phase mask. And then they are encoded by the first gyrator transform. The resulting information is again encrypted by a second gamma distribution random phase mask at the gyrator frequency plane. The final results are encoded by the second gyrator transform. Numerical simulations are presented to confirm the security, validity, and flexibility of the proposed idea. The gyrator transform rotation angle sensitivity test is also simulated. The occlusion and noise attacks analysis establish the scheme’s robustness. In gyrator transform-based optical image encryption cipher system, encrypting the input image with different parameters of gamma distribution RPMs will significantly change the statistical distribution of phase in the ciphertext. It means that the phase distribution in the ciphertext will not obey the law of random scattering medium. Therefore, it has potential to resist the attack based on the phase retrieval algorithm. Therefore, the security and flexibility of encryption can be improved by using gamma distribution RPMs.

Additive colors are interesting to young students. In this paper, we show a convenient and straightforward method to demonstrate this phenomenon by projector. It produces defocus blur and reduces imaging quality for color mixing. We believe this demonstration experiment can be performed in most classrooms.Additive colors are interesting to young students. In this paper, we show a convenient and straightforward method to demonstrate this phenomenon by projector. It produces defocus blur and reduces imaging quality for color mixing. We believe this demonstration experiment can be performed in most classrooms.

Phase-shifting interferometry is a kind of important technique used in optical interference metrology. This technique has high precision and good stability, which has been widely used in scientific research and industrial production. This paper proposes a new method to estimate global phase shift from two interferograms. This method performs algebraic calculation of two interferograms with the assistance of Hilbert transform. An iterative approach is used for the attempted phase to ensure that the minimum of assessment function is obtained. The simulated result indicate that the maximum calculation error of the global phase-shifting is 1.5%. And then we use experimental data to verify the performance of this method. The method proposed in this article is simple but precise, and can cope with interferograms with uneven background and modulation, non-periodic apodization, and random noises. It does not require any specific carrier frequency of the measured interferogram or any adjustment of range of integration in accordance with the carrier frequency.

The predecessor of China Optics was China Optics and Applied Optics Digest, which was founded in 1985. At that time, it was the only retrieval journal in the field of optics in China. At the end of 2008, China Optics and Applied Optics Digest was renamed 《中国光学》的前身是1985年创办的《中国光学与应用光学文摘》，当时是国内光学领域唯一的检索刊物。2008年底《中国光学与应用光学文摘》转型更名为《中国光学与应用光学》期刊，刊载内容突破了文摘的限制，正式成为学术刊物。