A non-contact 3D measuring system is configured to provide a combined three-dimensional shape of an object to be imaged based on a frame image, which has been captured by a camera while a measuring head is being scanned in an optical axis (Z-axis) direction, and the information on the position at which the image has been acquired. The system includes: a position detector for detecting a scanning position of the measuring head while a plurality of raw images are captured; and a computer for generating an interpolation image by linear interpolation for the captured raw image using the information of the scanning position as well as generating a combined frame image using the interpolation image.

A non-contact 3D measuring system is configured to provide a combined three-dimensional shape of an object to be imaged based on a frame image, which has been captured by a camera while a measuring head is being scanned in an optical axis (Z-axis) direction, and the information on the position at which the image has been acquired. The system includes: a position detector for detecting a scanning position of the measuring head while a plurality of raw images are captured; and a computer for generating an interpolation image by linear interpolation for the captured raw image using the information of the scanning position as well as generating a combined frame image using the interpolation image.

Various embodiments are provided which relate to the field of image signal processing, specifically relating to the generation of a depth-view image of a scene from a set of input images of a scene taken at different cameras of a multi-view imaging system. A method comprises obtaining a frame of an image of a scene and a frame of a depth map regarding the frame of the image. A minimum depth and a maximum depth of the scene and a number of depth layers for the depth map are determined. Pixels of the image are projected to the depth layers to obtain projected pixels on the depth layers; and cost values for the projected pixels are determined. The cost values are filtered and a filtered cost value is selected from a layer to obtain a depth value of a pixel of an estimated depth map.

Various embodiments are provided which relate to the field of image signal processing, specifically relating to the generation of a depth-view image of a scene from a set of input images of a scene taken at different cameras of a multi-view imaging system. A method comprises obtaining a frame of an image of a scene and a frame of a depth map regarding the frame of the image. A minimum depth and a maximum depth of the scene and a number of depth layers for the depth map are determined. Pixels of the image are projected to the depth layers to obtain projected pixels on the depth layers; and cost values for the projected pixels are determined. The cost values are filtered and a filtered cost value is selected from a layer to obtain a depth value of a pixel of an estimated depth map.

The disclosure relates to an image processing apparatus for determining a depth of a pixel of a reference image of a plurality of images representing a visual scene relative to a plurality of locations, wherein the plurality of locations define a two-dimensional grid with rows and columns and wherein the location of the reference image is associated with a reference row and a reference column of the grid. The image processing apparatus comprises a depth determiner configured to determine a first depth estimate on the basis of the reference image and a first subset of the plurality of images for determining the depth of the pixel of the reference image, wherein the images of the first subset are associated with locations being associated with a row of the grid different than the reference row and with a column of the grid different than the reference column.

The disclosure relates to an image processing apparatus for determining a depth of a pixel of a reference image of a plurality of images representing a visual scene relative to a plurality of locations, wherein the plurality of locations define a two-dimensional grid with rows and columns and wherein the location of the reference image is associated with a reference row and a reference column of the grid. The image processing apparatus comprises a depth determiner configured to determine a first depth estimate on the basis of the reference image and a first subset of the plurality of images for determining the depth of the pixel of the reference image, wherein the images of the first subset are associated with locations being associated with a row of the grid different than the reference row and with a column of the grid different than the reference column.

Embodiments of systems and methods for multi-aperture ranging are disclosed. An embodiment of a device includes a main lens, configured to receive an image from the field of view of the main lens, a multi-aperture optical component having optical elements optically coupled to the main lens and configured to create a multi-aperture image set that includes a plurality of subaperture images, wherein at least one point in the field of view is captured by at least two of the subaperture images, an array of sensing elements, a ROIC configured to receive the signals, to convert the signals to digital data, and to output the digital data, and an image processing system, responsive to the digital data that is output from the ROIC, which is configured to generate disparity values that correspond to at least one point in common between the at least two subaperture images.

A plenoptic camera captures a plenoptic image of an object illuminated by a point source (preferably, collimated illumination). The plenoptic image is a sampling of the four-dimensional light field reflected from the object. The plenoptic image is made up of superpixels, each of which is made up of subpixels. Each superpixel captures light from a certain region of the object (i.e., a range of x,y spatial locations) and the subpixels within a superpixel capture light propagating within a certain range of directions (i.e., a range of u,v spatial directions). Accordingly, optical properties estimation, surface normal reconstruction, depth estimation, and three-dimensional rendering can be provided by processing only a single plenoptic image. In one approach, the plenoptic image is used to estimate the bidirectional reflectance distribution function (BRDF) of the object surface.

A plenoptic camera captures a plenoptic image of an object illuminated by a point source (preferably, collimated illumination). The plenoptic image is a sampling of the four-dimensional light field reflected from the object. The plenoptic image is made up of superpixels, each of which is made up of subpixels. Each superpixel captures light from a certain region of the object (i.e., a range of x,y spatial locations) and the subpixels within a superpixel capture light propagating within a certain range of directions (i.e., a range of u,v spatial directions). Accordingly, optical properties estimation, surface normal reconstruction, depth estimation, and three-dimensional rendering can be provided by processing only a single plenoptic image. In one approach, the plenoptic image is used to estimate the bidirectional reflectance distribution function (BRDF) of the object surface.

A system and method can include receiving a set of views, encoding the set of views, and displaying the set of views such that they are perceived as a holographic image.