Related papers: Single-shot wide-field optical section imaging

Integral-field spectroscopy is the most effective method of exploiting the superb image quality of the ESO-VLT, allowing complex astrophysical processes to be probed on the angular scales currently accessible only for imaging data, but with…

Medical image segmentation is vital to the area of medical imaging because it enables professionals to more accurately examine and understand the information offered by different imaging modalities. The technique of splitting a medical…

Non-Line-of-Sight (NLOS) imaging allows to observe objects partially or fully occluded from direct view, by analyzing indirect diffuse reflections off a secondary, relay surface. Despite its many potential applications, existing methods…

We present a new interferometric imaging approach that allows for multiple-depth imaging in a single acquisition, using off-axis low-coherence holographic multiplexing. This technique enables sectioned imaging of multiple slices within a…

Optical imaging systems are generally limited by the depth of field because of the nature of the optics. Therefore, extending depth of field (EDoF) is a fundamental task for meeting the requirements of emerging visual applications. To solve…

High-resolution optical imaging methods, such as confocal microscopy and full-field optical coherence tomography, capture flat optical sections of the sample. If the sample is curved, the optical field sections through several sample layers…

Ultrafast single-shot imaging techniques now reach frame rates of tens of tera-frame-per-second (Tfps) and long sequence depths but are often too complex for large-scale use, both in terms of image acquisition and reconstruction. We propose…

Quantitative phase imaging has become a topic of considerable interest in the microscopy community. We have recently described one such technique based on the use of a partitioned detection aperture, which can be operated in a single shot…

Image segmentation has long been a basic problem in computer vision. Depth-wise Layering is a kind of segmentation that slices an image in a depth-wise sequence unlike the conventional image segmentation problems dealing with surface-wise…

The combination of different imaging modalities into single imaging platforms has a strong potential in biomedical sciences since it permits the analysis of complementary properties of the target sample. Here, we report on an extremely…

In this paper a hybrid image defogging approach based on region segmentation is proposed to address the dark channel priori algorithm's shortcomings in de-fogging the sky regions. The preliminary stage of the proposed approach focuses on…

Recent advances in Vision Transformers (ViT) and Stable Diffusion (SD) models with their ability to capture rich semantic features of the image have been used for image correspondence tasks on natural images. In this paper, we examine the…

We proposes a novel single-shot high dynamic range imaging scheme with spatially varying exposures (SVE) considering hue distortion. Single-shot imaging with SVE enables us to capture multi-exposure images from a single-shot image, so high…

Image segmentation is the process of partitioning an image into a set of meaningful regions according to some criteria. Hierarchical segmentation has emerged as a major trend in this regard as it favors the emergence of important regions at…

Image stitching is a classical and crucial technique in computer vision, which aims to generate the image with a wide field of view. The traditional methods heavily depend on the feature detection and require that scene features be dense…

Multifocus microscopy enables recording of entire volumes in a single camera exposure. In dense samples, multifocus microscopy is severely hampered by background haze. Here, we introduce a scalable multifocus method that incorporates…

In this work the method of masks, creating and using of inverted image masks, together with binary operation of image data are used in edge detection of binary images, monochrome images, which yields about 300 times faster than ordinary…

Paradoxically, imaging with resolution much below the wavelength $\lambda$ - now common place in the visible spectrum - remains challenging at lower frequencies, where arguably it is needed most due to the large wavelengths used. Techniques…

Lenses that can collect the perfect image of an object must restore propagative and evanescent waves. However, for efficient information transfer, e.g., in compressed sensing, it is often desirable to detect only the fast spatial variations…

Enlarging input images is a straightforward and effective approach to promote small object detection. However, simple image enlargement is significantly expensive on both computations and GPU memory. In fact, small objects are usually…