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This study explores the use of photometric techniques (shape-from-shading and uncalibrated photometric stereo) for upsampling the low-resolution depth map from an RGB-D sensor to the higher resolution of the companion RGB image. A…
Ray tracing is increasingly utilized in wireless system simulations to estimate channel paths. In large-scale simulations with complex environments, ray tracing at high resolution can be computationally demanding. To reduce the computation,…
We introduce a new spectral method for image segmentation that incorporates long range relationships for global appearance modeling. The approach combines two different graphs, one is a sparse graph that captures spatial relationships…
Imaging techniques based on single-pixel detection, such as ghost imaging, can reconstruct or recognize a target scene from multiple measurements using a sequence of random mask patterns. However, the processing speed is limited by the low…
Removing stripe noise, i.e., destriping, from remote sensing images is an essential task in terms of visual quality and subsequent processing. Most existing destriping methods are designed by combining a particular image regularization with…
Hyperspectral microscopy is an imaging technique that provides spectroscopic information with high spatial resolution. When applied in the relevant wavelength region, such as in the infrared (IR), it can reveal a rich spectral fingerprint…
Future radar systems are expected to use waveforms of a high bandwidth, where the main advantage is an improved range resolution. In this paper, a technique to design robust wideband waveforms for a Multiple-Input-Single-Output system is…
In this paper, we present a novel method for 3D geometric scene graph generation using range sensors and RGB cameras. We initially detect instance-wise keypoints with a YOLOv8s model to compute 6D pose estimates of known objects by solving…
Ghost imaging is an unconventional imaging technique that generates high resolution images by correlating the intensity of two light beams, neither of which independently contains useful information about the shape of the object. Ghost…
Signal recovery from nonlinear measurements involves solving an iterative optimization problem. In this paper, we present a framework to optimize the sensing parameters to improve the quality of the signal recovered by the given iterative…
Imaging through a single optical fiber offers attractive possibilities in many applications such as microendoscopy or remote sensing. However, the direct transmission of an image through an optical fiber is difficult because spatial…
Active stereovision systems for the 3D measurement of surfaces rely on the sequential projection of different fringe patterns onto the scene to robustly and accurately generate 3D surface data. This limits the temporal resolution to the…
In this paper, we introduce a novel deep neural network suitable for multi-scale analysis and propose efficient model-agnostic methods that help the network extract information from high-frequency domains to reconstruct clearer images. Our…
The newly emerging theory of compressed sensing (CS) enables restoring a sparse signal from inadequate number of linear projections. Based on compressed sensing theory, a new algorithm of high-resolution range profiling for…
In this paper we study a realistic setup for phase retrieval, where the signal of interest is modulated or masked and then for each modulation or mask a diffraction pattern is collected, producing a coded diffraction pattern (CDP) [CLM13].…
We describe a novel method for blind, single-image spectral super-resolution. While conventional super-resolution aims to increase the spatial resolution of an input image, our goal is to spectrally enhance the input, i.e., generate an…
We demonstrate the acquisition of stimulated Raman scattering spectra with the use of a single femtosecond pulse. High resolution vibrational spectra are obtained by shifting the phase of a narrow band of frequencies in the broadband input…
Different from traditional hyperspectral super-resolution approaches that focus on improving the spatial resolution, spectral super-resolution aims at producing a high-resolution hyperspectral image from the RGB observation with…
Recent research has demonstrated new capabilities in radio frequency (RF) sensing that apply to health care, smart home, and security applications. However, previous work in RF sensing requires heavy utilization of the radio spectrum, for…
Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the- art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate ---…