An imaging device includes a light separator that separates light into light bands, and imaging elements that each receives one of the light bands and generates a corresponding signal. Each of the imaging elements has a pixel size of at most 2.5 μm by 2.5 μm. A registration error among the imaging elements is equal to or less than a threshold determined according to the pixel size.

An image acquisition apparatus includes a first image sensor configured to obtain a first image based on detection of a light of a first wavelength band; a second image sensor configured to obtain a second image based on detection of a light of a second wavelength band that is wider than the first wavelength band; and a processor configured to obtain a third image having a spatial resolution corresponding to the first image and a color gamut corresponding to the second image based on the first image and the second image. The image acquisition apparatus may provide an image with a high spatial resolution and a wide color gamut.

Systems and methods are provided for generating calibration information for a media projector. The method includes tracking at least position of a tracking apparatus that can be positioned on a surface. The media projector shines a test spot on the surface, and the test spot corresponds to a known pixel coordinate of the media projector. The system includes a computing device in communication with at least two cameras, wherein each of the cameras are able to capture images of one or more light sources attached to an object. The computing device determines the object's position by comparing images of the light sources and generates an output comprising the real-world position of the object. This real-world position is mapped to the known pixel coordinate of the media projector.

Separations or images relating to film or other fields may be registered using a variety of features, such as, for example: (1) correcting one or more film distortions; (2) automatically determining a transformation to reduce a film distortion; (3) applying multiple criteria of merit to a set of features to determine a set of features to use in determining a transformation; (4) determining transformations for areas in an image or a separation in a radial order; (5) comparing areas in images or separations by weighting feature pixels differently than non-feature pixels; (6) determining distortion values for transformations by applying a partial distortion measure and/or using a spiral search configuration; (7) determining transformations by using different sets of features to determine corresponding transformation parameters in an iterative manner; and (8) applying a feathering technique to neighboring areas within an image or separation.

In an image processing method, an image processing device obtains an input image from an image sensor. Each pixel of the input image is either a type-I pixel or a type-II pixel. Each type-I pixel carries a luminance channel value and no color data, and each type-II pixel carries a single color channel value and no luminance data, wherein the single color channel value is a cyan channel value, a magenta channel value, or a yellow channel value. The image processing device generates a target image by performing interpolation based on the luminance channel values and the single color channel values of the pixels of the input image, wherein each pixel in the target image corresponds in location to a pixel in the input image and has three color channel values generated by the interpolation.

In order to perform image processing in which relative positional deviation of image outputs between two image pickup units is suppressed, an image pickup apparatus comprises: an imaging device that has a first image pickup unit configured to perform imaging in a first cycle and generate a first image signal, and a second image pickup unit configured to perform imaging in a second cycle shorter than the first image pickup unit and generate a plurality of second image signals; a relation degree information generation unit configured to generate relation degree information between the first image signal and the second image signal based on overlap between an exposure time period in the first image pickup unit and an imaging timing in the cycle of the second image pickup unit; a region selection unit configured to select a specific region from among the second image signals based on the relation degree information generated by the relation degree information generation unit; and an image processing unit configured to perform predetermined image processing on the first image signal based on the specific region selected by the region selection unit.

A camera module aligning method includes the following steps. Firstly, a reference chart having plural chart characteristic points is provided. Then, a camera module is used to shoot the reference chart, and an installation position and an installation posture of the camera module are acquired according to an internal parameter matrix and an external parameter matrix. When the camera module shoots the reference chart and an image is formed on an imaging plane of the camera module, a relationship between at least one image characteristic point of the image and the corresponding chart characteristic point complies with a standard relationship. The standard relationship is defined by the internal parameter matrix and the external parameter matrix.

A camera module aligning method includes the following steps. Firstly, a reference chart having plural chart characteristic points is provided. Then, a camera module is used to shoot the reference chart, and an installation position and an installation posture of the camera module are acquired according to an internal parameter matrix and an external parameter matrix. When the camera module shoots the reference chart and an image is formed on an imaging plane of the camera module, a relationship between at least one image characteristic point of the image and the corresponding chart characteristic point complies with a standard relationship. The standard relationship is defined by the internal parameter matrix and the external parameter matrix.

A mechanism is described for facilitating sensors arrangement and shifting for multisensory super-resolution cameras in imaging environments, according to one embodiment. A method of embodiments, as described herein, includes arranging sensors of a camera such that pixel centers of pixels of an image are spread evenly across a pixel area having pixel planes corresponding to the sensors, where the image is captured by the camera. The method may further include re-arranging the sensors by dividing the sensors in pairs of sensors, where each pair of sensors corresponds to a pair of pixel planes, and shifting the sensors diagonally such that the corresponding pixel planes are adjusted accordingly for improving quality of the image.

The present invention provides an image processing device, an imaging apparatus, and an image processing method capable of acquiring images that are registered with high accuracy and include only a component of a desired wavelength range. In an image processing device according to an aspect of the invention, at least one image is captured with light having a plurality of wavelength ranges not overlapping one another (that is, including an intentional interference component in addition to a principal wavelength range), and at least one wavelength range of the plurality of wavelength ranges is common among the images. Accordingly, it is possible to detect correspondence points among a plurality of images based on information of such a common wavelength range, and to register the plurality of images with high accuracy. In addition, since an influence of light having a wavelength range other than a specific wavelength range is eliminated after registration, it is possible to acquire a plurality of images including only a component of a desired wavelength range.