Described herein are systems and methods for assessing a biological sample. The methods include: characterizing a speckled pattern to be applied by a diffuser; positioning a biological sample relative to at least one coherent light source such that at least one coherent light source illuminates the biological sample; diffusing light produced by the at least one coherent light source; capturing a plurality of illuminated images with the embedded speckle pattern of the biological sample based on the diffused light; iteratively reconstructing the plurality of speckled illuminated images of the biological sample to recover an image stack of reconstructed images; stitching together each image in the image stack to create a whole slide image, wherein each image of the image stack at least partially overlaps with a neighboring image; and identifying one or more features of the biological sample. The methods may be performed by a near-field Fourier Ptychographic system.

The present invention is applicable to the fields of panoramic images and videos, and provides a panoramic image and video splicing method, and a panoramic camera. In the present invention, fisheye photos captured by two adjacent cameras are mapped to corresponding seam areas of a sphere model, so as to form two strip graphs having overlapping areas; performing block template matching on the two strip graphs to obtain an initial template matching result; performing matching filtering on the initial template matching result by using an area expansion-based matching filtering algorithm, so as to obtain a final matching result; and updating a mapping relationship between the fisheye photos and the corresponding seam areas of the sphere model, and performing panoramic splicing according to the updated mapping relationship to obtain a seamless panoramic image.

Systems, processes, and techniques to automatically detect and enlarge a speaking one of plurality of participants on one side of a video conference. In at least one embodiment, the speaking participant is identified using one or more heuristics and/or one or more neural networks.

The present invention is directed to making it possible to reduce a possibility of image stitching failures. An information processing apparatus includes a feature extraction unit configured to extract feature points from each of a plurality of images of an object to be inspected captured from a plurality of viewpoints, an image quality evaluation unit configured to, for each of the plurality of images, evaluate whether an image quality based on a predetermined index satisfies allowable conditions for inspection works of the object, and an image stitching unit configured to stitch at least a part of the images, among the plurality of images, having the image quality that satisfies the allowable conditions according to a positional relation based on the feature points.

Techniques and apparatuses for highlighting media through weighting of people or contexts are described. This document describes techniques that allow a user to quickly and easily highlight media, such as through generating a highlight reel. The techniques also enable selection of context and person weightings by which to tailor highlight reels.

A digital camera and a method for aligning digital images comprising: receiving images including first and second images depicting a first and a second region of a scene, the regions being overlapping and displaced along a first direction; aligning the images using a transformation; determining disparity values for an overlap between the images; identifying misalignments by identifying blocks of pixels in the first image having a same position along a second direction and having disparity values exhibiting a variability lower than a first threshold and exhibiting an average higher than a second threshold; adjusting the transformation for the identified blocks of pixels in the first image and their matching blocks of pixels in the second image; and realigning the images using the adjusted transformation.

Techniques are described for using a smart phone or other mobile device to perform automated operations for generating panorama images of building environments and for subsequently using the generated panorama images in further automated manners. In at least some situations, the generation of a panorama image by a mobile device is based at least in part on automatically acquiring multiple constituent images on the mobile device in multiple directions from an acquisition location and on concurrently combining acquired constituent images on the mobile device, such as in a real-time manner relative to the constituent image capture, to generate a panorama image with 360° of horizontal coverage of the view from that acquisition location. Information about such identified building floor plans may be used in various automated manners, including for controlling navigation of devices (e.g., autonomous vehicles), for display on client devices in corresponding graphical user interfaces, etc.

Many embodiments can comprise a system. The system can comprise one or more processors and one or more storage devices. The one or more storage devices can be configured to store computing instructions that, when executed, cause the processor to receive a plurality of images of an object, the plurality of images comprising different views of the object from around the object; iteratively align one or more images within one or more subsets of the plurality of images until the object is aligned from image to image within the one or more subsets of the plurality of images; and selectively align respective images of the one or more subsets to each other to produce a surround image. Other embodiments are disclosed herein.

Methods and systems for milling and imaging a sample based on multiple fiducials at different sample depths include forming a first fiducial on a first sample surface at a first sample depth; milling at least a portion of the sample surface to expose a second sample surface at a second sample depth; forming a second fiducial on the second sample surface; and milling at least a portion of the second sample surface to expose a third sample surface including a region of interest (ROI) at a third sample depth. The location of the ROI at the third sample depth relative to the first fiducial may be calculated based on an image of the ROI and the second fiducial as well as relative position between the first fiducial and the second fiducial.

Image signal processing includes generating an exposure compensated image based on a gain value applied to an exposure level of a first image and a gain value applied to an exposure level of a second image. The gain value may be progressively increased from an approximate center of the first image to an edge of the first image to a common exposure level. The gain value may be progressively decreased from an approximate center of the second image to an edge of the second image to the common exposure level. Gain values may be scaled on each color channel for a pixel based on a saturation level of the pixel.