Related papers: Sub-pixel resolution with color X-ray camera SLcam…
We demonstrate spectroscopy of incoherent light with sub-diffraction resolution. In a proof-of-principle experiment we analyze the spectrum of a pair of incoherent point-like sources whose separation is below the diffraction limit. The two…
Hyperspectral image segmentation is crucial for many fields such as agriculture, remote sensing, biomedical imaging, battlefield sensing and astronomy. However, the challenge of hyper and multi spectral imaging is its large data footprint.…
Hyperspectral cameras face harsh trade-offs between spatial, spectral, and temporal resolution in inherently low-photon conditions. Computational imaging systems break through these trade-offs with compressive sensing, but have required…
Most of the existing learning-based single image superresolution (SISR) methods are trained and evaluated on simulated datasets, where the low-resolution (LR) images are generated by applying a simple and uniform degradation (i.e., bicubic…
We propose a new technique to obtain super-resolution images with radio interferometer using sparse modeling. In standard radio interferometry, sampling of ($u$, $v$) is quite often incomplete and thus obtaining an image from observed…
Spontaneous downconversion is a versatile source for correlated biphotons that has been employed in many quantum sensing and imaging experiments. Spatially-resolved photon-counting detectors allow to access a large number of modes, posing…
Time-of-flight three dimensional imaging is an important tool for many applications, such as object recognition and remote sensing. Unlike conventional imaging approach using pixelated detector array, single-pixel imaging based on projected…
Semantic segmentation, which aims to classify every pixel in an image, is a key task in machine perception, with many applications across robotics and autonomous driving. Due to the high dimensionality of this task, most existing approaches…
In recent years, the introduction of deep learning into the field of single-pixel imaging has garnered significant attention. However, traditional networks often operate within the pixel space. To address this, we innovatively migrate…
In this paper we aim to tackle the problem of reconstructing a high-resolution image from a single low-resolution input image, known as single image super-resolution. In the literature, sparse representation has been used to address this…
Coherent diffraction imaging is a high-resolution imaging technique whose potential can be greatly enhanced by applying the extrapolation method presented here. We demonstrate enhancement in resolution of a non-periodical object…
Coherent diffractive imaging is unique as the only route for achieving diffraction-limited spatial resolution in the extreme ultraviolet and X-ray regions, limited only by the wavelength of the light. Recently, advances in coherent short…
Capable of automated near real time superpixel detection and quality assessment in an uncalibrated monitor typical red green blue (RGB) image, depicted in either true or false colors, an original low level computer vision (CV) lightweight…
Wide-field survey instruments are used to efficiently observe large regions of the sky. To achieve the necessary field of view, and to provide a higher signal-to-noise ratio for faint sources, many modern instruments are undersampled.…
Scanning laser confocal holographic microscopy using a spatial heterodyne detection method is presented. Spatial heterodyne detection technique employs a Mach-Zehnder interferometer with the reference beam frequency shifted by two…
The primary aim of single-image super-resolution is to construct high-resolution (HR) images from corresponding low-resolution (LR) inputs. In previous approaches, which have generally been supervised, the training objective typically…
High-resolution satellite imagery has proven useful for a broad range of tasks, including measurement of global human population, local economic livelihoods, and biodiversity, among many others. Unfortunately, high-resolution imagery is…
It is demonstrated that non-constant kernel solution, that can fit the spatial variations of the kernel can be obtained with minimum computing time. The CPU cost required with this new extension of the image subtraction method is almost the…
Single-photon light detection and ranging (LiDAR), offering single-photon sensitivity and picosecond time resolution, has been widely adopted for active imaging applications. Long-range active imaging is a great challenge, because the…
Recent advancements in computer vision, particularly in detection, segmentation, and classification, have significantly impacted various domains. However, these advancements are tied to RGB-based systems, which are insufficient for…