Dual Optical Path Based Adaptive Compressive Sensing Imaging System

Compressive Sensing (CS) has proved to be an effective theory in the field of image acquisition. However, in order to distinguish the difference between the measurement matrices, the CS imaging system needs to have a higher signal sampling accuracy. At the same time, affected by the noise of the light path and the circuit, the measurements finally obtained are noisy, which directly affects the imaging quality. We propose a dual-optical imaging system that uses the bidirectional reflection characteristics of digital micromirror devices (DMD) to simultaneously acquire CS measurements and images under the same viewing angle. Since deep neural networks have powerful modeling capabilities, we trained the filter network and the reconstruction network separately. The filter network is used to filter the noise in the measurements, and the reconstruction network is used to reconstruct the CS image. Experiments have proved that the method we proposed can filter the noise in the sampling process of the CS system, and can significantly improve the quality of image reconstruction under a variety of algorithms.

Real-Time Geometric Glint Anti-Aliasing with Normal Map Filtering

Real-time geometric specular anti-aliasing is required when using a low number of pixel samples and high-frequency specular lobes. Several methods have been proposed for mono-lobe bidirectional reflection distribution functions (BRDFs), but none for multi-lobe BRDFs, e.g., a glinty BRDF. We present the first method for real-time geometric glint anti-aliasing (GGAA). It eliminates most of the inconsistent appearing and disappearing of glints on surfaces with significant curvatures during animations. The technique uses the glinty BRDF of Chermain et al. [2020] and leverages hardware GPU-filtering of textures to filter slope distributions on the fly. We also improve this glinty BRDF by adding a correlation factor of slope. This BRDF parameter allows convergence to normal distribution functions that are not aligned on the surface's axes. Above all, this parameter makes glint rendering compatible with normal map filtering using LEAN mapping. Using GGAA increases the rendering time from 0.6 % to 4.2 % and it requires 1/3 more memory due to MIP mapping of tabulated slope distributions. The results are compared with references using a thousand samples per pixel.

Simultaneous Measurement of BRDF and Surface Curvature by using Pattern Illumination

In this study, we propose the simultaneous measurement method of the bidirectional reflection distribution function (BRDF) and the radius of curvature by using pattern illumination. For nonplanar objects, the angle of reflection light changes according to the surface normal angle of curved object. Therefore, it is necessary to consider the effects of curved surfaces when measuring the BRDF on non-planar surfaces. We suppose a convex surface that can be represented by a constant radius of curvature. The pattern of illumination was generated by placing the illumination mask with pattern apertures in the incident light path of the BRDF measurement apparatus in which the incident light is collimated light. We developed the measurement apparatus. We measured four types of sample with different BRDFs on three different radiuses of curvature. The results showed that the BRDF and the radius of curvature can be measured simultaneously by using the pattern illumination.