A method, medical imaging workstation (1000) and hybrid medical imaging scanner (1100) are provided for defining a region of interest (RoI) for display on at least two medical scan images. When displaying a first medical scan image (740), input data defining a RoI on the image is captured, and stored as at least a first region representation (760). The RoI is displayed on a second medical scan image (750), based on the first region representation (760). Changes to the RoI on the second medical scan image (750) are used to update the first region representation (760). There may be separate region representations (760, 770) associated with each of several medical scan images. The invention may improve the definition of a region of interest, by allowing editing on each of multiple image displays (820, 830, 880) to feed through to all medical scan images.

A three-dimensional object detection device can enhance the accuracy in detecting a three-dimensional object regardless of the brightness in the detection environment. The device has an image capture means that captures an image of a predetermined area and an image conversion means that converts the image through a viewpoint conversion into birds-eye view image. A first three-dimensional object detection means aligns positions of bird's-eye view images at different times obtained by the image conversion means, counts the number of pixels that exhibit a predetermined difference on a differential image of the aligned bird's-eye view images to generate a frequency distribution thereby creating differential waveform information, and detects a three-dimensional object on the basis of the differential waveform information. A second three-dimensional object detection means detects edge information from the bird's-eye view image obtained by the image conversion means and detects a three-dimensional object on the basis of the edge information.

A device determines a Compact Multi-Pass Transform (CMPT) from a plurality of CMPTs. Additionally, the device decompresses CMPT parameters for the CMPT. In instances where the device decodes video data, the device applies the CMPT to a coefficient block to reconstruct a residual block and decodes, based on a predictive block and the residual block, a current block of a picture of the video data. In instances where the device encodes video data, the device applies the CMPT to a residual block to construct a coefficient block and generates for output information indicating coefficient values for the coefficient block.

As part of a video encoding or decoding process, a device applies a transformation to input data elements to derive output data elements for a current block. The transformation comprises a sequence of vector transformations. For each respective vector transformation of the sequence of vector transformations other than a first vector transformation of the sequence of vector transformations, input values for the respective vector transformation comprise output values of the respective previous vector transformation of the sequence of vector transformations. Each respective vector transformation of the sequence of vector transformations further takes, as input, a respective parameter vector for the respective vector transformation, the respective parameter vector for the respective vector transformation comprising one or more parameters.

A method of determining a reference calibration setting for an adaptive optics system (1) comprising a detecting device (8) for detecting light from an object (5); and at least one controllable wavefront modifying device (9) arranged such that light from the object (5) passes via the wavefront modifying device (9) to the detecting device (8). The method comprises the steps of: arranging (100) a light-source between the object (5) and the wavefront modifying device (9) to provide a reference light beam to the detecting device (8) via the wavefront modifying device; for each of a plurality of orthogonal wavefront modes of the wavefront modifying device: controlling (101) the wavefront modifying device to vary a magnitude of the orthogonal wavefront mode over a predetermined number of magnitude settings; acquiring (102) a series of readings of the detecting device, each reading corresponding to one of the magnitude settings; determining (103) a quality metric value indicative of an information content of the reading for each reading in the series of readings, resulting in a series of quality metric values; and determining (106) a reference parameter set for the wavefront modifying device corresponding to an optimum quality metric value based on the series of quality metric values.

In general, the subject matter described in this disclosure can be embodied in methods, systems, and program products for detecting motion in images. A computing system receives first and second images that were captured by a camera. The computing system generates, using the images, a mathematical transformation that indicates movement of the camera from the first image to the second image. The computing system generates, using the first image and the mathematical transformation, a modified version of the first image that presents the scene that was captured by the first image from a position of the camera when the second image was captured. The computing system determines a portion of the first image or second image at which a position of an object in the scene moved, by comparing the modified version of the first image to the second image.

For deblurring an image, a method records both short-exposed pixels at a higher frame rate for a short-exposure region and normal-exposed pixels at a normal frame rate for full resolution. In addition, the method deblurs a normal-exposed image as a function of the short-exposed pixels and the normal-exposed pixels.

A hyperspectral facial analysis system and method for personalized health scoring to assess the risk that a person has a disease. Embodiments capture images in multiple spectral bands, such as visible, infrared, and ultraviolet, and analyze these images to generate multiple health metrics, such as pallor, temperature, sweat, and chromophores. These metrics may be combined into an overall health score that may be used for screening. Image analysis may focus on the area under the eyes, where skin is thinnest. Images may be compared to a reference population to identify anomalous values, so that health scoring automatically adjusts for local conditions. Pallor may be calculated based on hue and saturation of visible light images. Temperature may be calculated based on infrared image intensity. Sweat may be calculated using cross-polarized images to identify specular highlights. Chromophores may be calculated by comparing frequency domain ultraviolet images to those of the reference population.

An image processing apparatus according to the present application includes a reception unit and a specification unit. The reception unit receives image data produced through image capturing by a predetermined image capturing apparatus and including an elliptical figure. The specification unit performs projection transform of the image data so that the elliptical figure included in the image data received by the reception unit appears to be an exact circle, and specifies, based on characteristic information on the exact circle obtained through the projection transform, the exact circle to be a marker used in predetermined processing on the image data.

It is possible to consider an image as a composite wave that is the result of layering waves having differing periods and amplitudes. An image captured via a lens having a water droplet attached thereto has a higher occurrence of changes such as image blur than an image that does not have a water droplet attached thereto, which means that this type of change in an image results in changes in the composite wave thereof as well. Provided is a lens dirtiness detection device that suitably determines whether a lens is dirty without being affected by a background image by: focusing on the occurrence of large changes in the composite wave of an image that accompany an increase in the dirtiness of a camera lens; extracting each of the image frequency components that constitute the composite wave; and analyzing changes in the magnitude relation between the frequency components.