Abstract:
An image processing device for generating an output image front an input image of a scene, the input image being the first image and the output image being the second image, the output image corresponds to an exposure that is different from an exposure of the input image, the image processing device comprising an intensity transformer that is configured to determine one or more intensities of an output pixel of the output image based on an input patch around an input pixel of the input image that corresponds to the output pixel.
Abstract:
An image processing device for generating an output image front an input image of a scene, the input image being the first image and the output image being the second image, the output image corresponds to an exposure that is different from an exposure of the input image, the image processing device comprising an intensity transformer that is configured to determine one or more intensities of an output pixel of the output image based on an input patch around an input pixel of the input image that corresponds to the output pixel.
Abstract:
An image processing system for generating a high dynamic range image from a first image and a second image is presented. The system comprises a first displacement estimator adapted to estimate a displacement of image content between a reference image derived from the first image and an image to be warped derived from the second image. The system comprises a first warping unit that compensates the estimated displacement by warping the image to be warped resulting in a first warped image. The system comprises a first error detector adapted to detect geometric warping errors within the first warped image and a first error compensator adapted to compensate the estimated geometric warping errors within the first warped image resulting in a first error corrected image. The system comprises a high dynamic range calculator adapted to calculate the high-dynamic range image based upon the first error corrected image and the reference image.
Abstract:
An apparatus for generating a model for pose estimation of a system obtains training data for a multiple locations. The training data includes one or more images captured by an image capturing device and the respective poses of the captured images. At least one data sample is generated from the training data for each of the captured images, where a data sample for an image is an assignment of the image and at least one other image selected from the training data to respective poses. A neural network is trained with a data set made up of the data samples to estimate a respective pose of a localization image from: the localization image; at least one additional image from the training data; and a respective pose of each of additional image.
Abstract:
A computer implemented method of estimating depth for an image and relative camera poses between images in a video sequence, includes backwards warping the source image to generate a first reconstructed target image, and calculating an initial image reconstruction loss based on the target image and the first reconstructed target image. Forward warping the source depth map is performed to generate a second reconstructed target depth map, and an occlusion mask is generated based on the second reconstructed target depth map. The method further includes regularising the initial image reconstruction loss based on the generated occlusion mask. Thus, an occlusion aware method of image reconstruction is provided via a combination of forward and backward warping which identifies and masks occluded areas, and regularizes the image reconstruction loss.
Abstract:
A focus tunable optical system includes a compound lens, which includes a plurality of focus tunable lenses. Further, the focus tunable optical system includes a controller, which is configured to shift a focus of the compound lens from a first focal plane to a second focal plane. To this end, the controller is configured to apply, individually to each focus tunable lens of the plurality of the focus tunable lenses, a control signal having a first value for the first focal plane and a second value for the second focal plane.
Abstract:
A method and an apparatus for generating a High Dynamic Range, HDR, image are proposed. The method comprises obtaining a set of two or more input images, the two or more input images including a reference image and one or more non-reference images; for each of the one or more non-reference images, performing an image analysis which comprises, for each region of a plurality of regions of the non-reference image, assessing whether the region of the non-reference image and a corresponding region of the reference image show the same image content and declaring the region of the non-reference image as valid or as invalid based on the assessment; and generating the HDR image by fusing the reference image and the one or more non-reference images, wherein the fusing comprises, for each of the one or more non-reference images, disregarding the invalid regions of the respective non-reference image.
Abstract:
An image processing apparatus for processing a digital image, where the digital image comprises a reference block and a plurality of further blocks, and where the image processing apparatus comprises a determiner being configured to determine a plurality of similarity measures between the reference block and the plurality of further blocks, wherein each similarity measure indicates a similarity between a noise distribution in the reference block and a noise distribution in a further block of the plurality of further blocks, and the determiner being further configured to determine a plurality of similar blocks from the plurality of further blocks upon the basis of the plurality of similarity measures.
Abstract:
A data processing apparatus for determining a pose of an image capturing device based on an image of a three dimensional (3D) scene is disclosed. The data processing apparatus comprises a processing circuitry configured to: select a plurality of key two dimensional (2D) points of a plurality of 2D points of the image based on a respective score of each of the plurality of 2D points; determine at least for a subset of the plurality of 2D points of the image a respective feature vector for obtaining a plurality of feature vectors; concatenate the image with the plurality of feature vectors for obtaining an intermediate tensor; determine a plurality of 3D points of the 3D scene based on the intermediate tensor; and determine the pose based on the plurality of key 2D points of the image and the plurality of 3D points of the 3D scene using a Perspective-n-Point scheme.
Abstract:
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.