Thermal radiation control has attracted increasing attention in a wide range of field, including infrared detection, radiative cooling, thermal management, and thermal camouflage. Previously reported thermal emitters for thermal camouflage presented disadvantages of lacking either tunability or thermal stability. In this paper, we propose a tunable thermal emitter consisting of metal-insulator-metal (MIM) plasmonic metamaterial based on phase-change material Ge₂Sb₂Te₅ (GST) to realize tunable control of thermal radiation in wavelength ranges from 3 μm to 14 μm. Meanwhile, the proposed thermal emitter possesses near unity emissivity at the wavelength of 6.3 μm to increase radiation heat dissipation, maintaining the thermal stability of the system. The underlying mechanism relies on fundamental magnetic resonance and the interaction between the high-order magnetic resonance and anti-reflection resonance. When the environmental background is blackbody, the tunable emitter maintains signal reduction rates greater than 80% in middle-IR and longer-IR regions from 450 K to 800 K and from room temperature to 800 K, respectively. The dependences of thermal camouflage on crystallization fraction of GST, incident angles and polarization angles have been investigated in detail. In addition, the thermal emitter can continuously realize thermal camouflage for various background temperatures and environmental background in atmospheric window in the range of 3–5 μm.

Imaging through scattering media faces great challenges. Object information will be seriously degraded by scattering media, and the final imaging quality will be poor. In order to improve imaging quality, we propose using the transmitting characteristics of an object’s polarization information, to achieve imaging through scattering media under natural light using an improved U-net. In this paper, we choose ground glass as the scattering medium and capture the polarization images of targets through the scattering medium by a polarization camera. Experimental results show that the proposed model can reconstruct target information from highly damaged images, and for the same material object, the trained network model has a superior generalization without considering its structural shapes. Meanwhile, we have also investigated the effect of the distance between the target and the ground glass on the reconstructing performance, in which, and although the mismatch distance between the training set and the testing sample expands to 1 cm, the modified U-net can also efficaciously reconstruct the targets.

Compared with the standard depolarization index, indices of polarimetric purity (IPPs) have better performances to describe depolarization characteristics of targets with different roughnesses of interfaces under different incident angles, which allow us a further analysis of the depolarizing properties of samples. Here, we use IPPs obtained from different reflective interfaces as a criterion of depolarization property to characterize and classify targets covered by organic paint layers with different roughness. We select point-light source as radiation source with wavelength as 632.8 nm, and four samples, including Cu, Au, Al and Al₂O₃, covered by an organic paint layer with refractive index of n = 1.46 and Gaussian roughness of α = 0.05~0.25. Under different incident angles, the values of P₁, P₂, P₃ at divided 90 × 360 grid points and their mean values in upper hemisphere have been obtained and discussed in the IPPs space. The results show that the depolarization performances of the different reflective interfaces (materials, incident angles and surface roughness) are unique in IPPs space, providing us with a new avenue to analyze and characterize different targets.