Semantic segmentation of Mars scenes has a crucial role in Mars rovers science missions. Current CNN-based composition of U-Net has powerful information extraction capabilities; however, convolutional localization suffers from the limited global context modeling capability. Although Transformer global modeling has performed well, it still encounters obstacles in the extraction and retention of low-level features. This issue is particularly relevant for Martian rocks with their varying shapes, textures, and sizes in Mars scenes. In this paper, we propose a novel Transformer semantic segmentation framework for Martian rock images, called MarsFormer, that consists of an encoder-decoder structure connected through a Feature Enhancement Module (FEM) and a Window Transformer Block (WTB). Specifically, multi-scale hierarchical features are generated by the Mix Transformer encoders, Upgraded-FFN decoder (UFD) fuses and filters features at different scales, preserving the rich local and global contextual information. FEM enhances the inter-multi-scale feature correlation from both spatial and channel perspectives. WTB captures the long-range contexts and preserves the local features. We built two datasets of synthetic and real Martian rocks. The synthetic dataset is SynMars, referencing data from the ZhuRong rover taken from its Virtual Terrain Engine. The other dataset is MarsData-V2, from real Mars scenes, and published recently in our previous study. Extensive experiments conducted on both datasets showed that MarsFormer achieves superiority in Martian rock segmentation, obtaining state-of-the-art performance with favorable computational simplicity. The data is available at: https://github.com/CVIR-Lab/SynMars.

This article presents two kernel-based rock detection methods for a Mars rover. Rock detection on planetary surfaces is particularly pivotal for planetary vehicles regarding navigation and obstacle avoidance. However, the diverse morphologies of Martian rocks, the sparsity of pixel-wise features, and engineering constraints are great challenges to current pixel-wise object detection methods, resulting in inaccurate and delayed object location and recognition. We therefore propose a region-wise rock detection framework and design two detection algorithms, kernel principle component analysis (KPCA)-based rock detection (KPRD) and kernel low-rank representation (KLRR)-based rock detection (KLRD), using hypotheses of feature and sub-spatial separability. KPRD is based on KPCA and is expert in real-time detection yet with less accurate performance. KLRD is based on KPRD with KLRR which can generate more precise rock detection results with less delay. To validate the efficiency of the proposed methods, we build a small-scale Martian rock dataset, MarsData, containing various rocks. Preliminary experimental results show that our methods are efficient in dealing with complex images containing rocks, shadows, and gravel. The code and data are available at: https://github.com/CVIR-Lab/MarsData.

Multifunctional antireflective coatings have practical applications as important optical components in many fields, particularly for optical devices and imaging systems. However, a good antireflection application in the visible region is often unsatisfactory for mid-infrared devices, and the difficulty in obtaining multiple capabilities simultaneously is one of the main factors limiting their applications. In this work, hierarchical moth-eye structures with superhydrophobicity were fabricated via inductively coupled plasma reactive ion etching (ICP-RIE) using nanodisk-array masks, which were formed by three-beam laser interference lithography (LIL), for improving the ultra-broadband optical properties. The uniform antireflection efficiency, which was close to 1% reflectivity covering over the visible and mid-infrared wavelength range, was exhibited by the moth-eye structures with high-quality pillar arrays. Additionally, irregular nanostructures were tailored onto the top of the pillars to generate hierarchical moth-eye structures for simultaneously obtaining both the superhydrophobic and anticorrosive properties. The fabricated antireflective structures, with the features of self-cleaning and durability, have the advantage of being for long-term use in harsh environments.

The output polarization states of corner cubes (for both uncoated and metal-coated surfaces) with an input beam of arbitrary polarization state and of arbitrary tilt angle to the cube have been analyzed by using the three-dimensional polarization ray-tracing matrix method. The diattenuation and retardance of the corner-cube retroreflector (CCR) for all six different ray paths are calculated, and the relationships to the tilt angle and the tilt orientation angle are shown. When the tilt angle is large, hollow metal-coated CCR is more appropriate than solid metal-coated CCR for the case that the polarization states of output beam should be controlled.

Reflection loss on the optical component surface is detrimental to performance. Several researchers have discovered that the eyes of moths are covered with micro- and nanostructured films that reduce broadband and wide-angle light reflection. This research proposes a new type of moth-eye subwavelength structure with a waist, which is equivalent to a gradient refractive index film layer with high–low–high hyperbolic-type fill factor distribution. The diffraction order characteristics of a moth-eye subwavelength structure are first analyzed using a rigorous coupled wave analysis. The moth-eye structural parameters are optimized within the spectral range of 2–5 μm using the finite-difference time-domain method. The experimental fabrication of the moth-eye structure with a waist array upon a silicon substrate is demonstrated by using three-beam laser interferometric lithography and an inductively coupled plasma process. The experimental and simulation results show good agreement. The experimental results show that the reflectivity of the moth-eye structure with a waist is less than 1.3% when the incidence angle is less than 30°, and less than 4% when the incidence angle is less than 60°. This research can guide the development of AR broadband optical components and wide-angle applications.

Multiring pure-phase binary optical elements (BOEs) are widely used to extend the depth of focus (DOF) in many optical applications. Although researchers have designed various BOEs to extend the DOF, few theories and experiments have been reported to validate the performances of different N-ring pure-phase BOEs to realize the DOF as long as possible. In this paper, aberration theory is used to obtain the simple and straightforward initial phase, and a novel modified Gerchberg–Saxton algorithm is presented for generating N-ring $0\text{-}\pi$-phase BOEs to optimally extend the DOF. Theoretical, numerical, and experimental results demonstrate that the DOF can be extended with increased N in the same NA.