Dual Imaging–Can Virtual Be Better Than Real?

Abstract

In this paper, a dual imaging technique is used for high-precision reconstruction of an observed 3D scene. In contrast to stereo vision, dual imaging systems use a camera and a projector instead of a camera pair. We propose a multiresolution approach based on the sum-to-one transform, coupled with compressive sensing principles, for efficient estimation of the light transport matrix (LTM). The LTM contains information on both optical systems and the 3D scene. In our setup, the camera sensor is intentionally chosen to be low resolution to prove the future use of inexpensive sensors in nonvisible regions of the light spectrum, as well as the potential design of simplified multiview and light field acquisition systems. We show that a highprecision estimation of the LTM from a reduced set of measurements is possible. Virtual measurements, instead of physical, are conducted to obtain the 3D reconstruction. We show that 3D scene reconstruction from the proposed virtual measurements corresponds with the actual physical acquisition. Moreover, this approach provides much more detail in the reconstruction. The computational complexity of the proposed methods is reduced to such a level that practical implementations are feasible.

[Retracted] Application of GIS and Multisensor Technology in Green Urban Garden Landscape Design

“…With the continuous improvement of people's material and living water quality and the change of the main contradictions in Chinese society, people's appreciation level has also been continuously enhanced, and higher requirements have been put forward for aesthetic appreciation, leisure health care and health recuperation. As the artery of the city, the road is the most frequent place for urban people to move and use and the most user-involved environmental space in urban garden landscape design [1]. Under the current social situation, urban residents are under great pressure in life and work, and they are eager for some places where their lives and work can be satisfied; the second road environment is the place where urban residents have the most contact and stay for the longest time in their life and work.…”

Single-Pixel Compressive Imaging in Shift-Invariant Spaces via Exact Wavelet Frames

“…A signal with a low information rate can be exactly recovered from far fewer measurements (samples) in the CS framework than in the conventional sampling frameworks, even if it has a high innovation rate. The theory of CS has led to the enhancement of signal reconstructions in low-resolution imaging devices [35] and in medical devices where the full measurements are missing or not available (e.g., magnetic resonance imaging [36], computed tomography, etc. ).…”

“…for constants 0 < α ≤ β < ∞. In this paper, the sampling kernel and the signal generator are imposed to form Riesz bases, and thus the sensing matrix Θ := SR Ψ satisfy the condition (35). A more convenient property of Θ that provide a concrete measure of its recovery ability is the mutual coherence.…”

“…However, for complex scenes with a lot of details, the number of measurements is enormous if one wants to obtain high-quality reconstruction results in 256 × 256 resolution. In order to efficiently and realistically simulate measurements for a high-detail scene, we use the principle of dual photography [50] and estimate light transport matrix (LTM) between the camera and the projector by following the procedure reported in [35]. We compute the high-resolution LTM between the projector of resolution 256 × 256 and the camera of resolution 128 × 128 with only a fraction of measurements and use it to calculate the light transport between the projector and an imaginary single-pixel detector at the camera location.…”