Abstract: A method for suppressing chromatic aberration, especially blue or red fringing, in a digital image with multiple color channels is disclosed. The method comprises negatively correcting a first color channel by subtracting an overshoot component of the first color channel. The subtraction is subject to a lower threshold, which is dependent on a local value of at least one further color channel.

Abstract: The present disclosure relates to a method performed by a deviation analyzing system (1) for black level drift assessment of a digital camera image sensor (21). The deviation analyzing system measures (1001) for pixels of an image captured by the image sensor, a respective luminance value and corresponding chromaticity value of each pixel. The deviation analyzing system further determines (1002) a respective average chromaticity value for differing luminance levels of the measured luminance values, based on for each luminance level averaging the corresponding measured chromaticity values. Moreover, the deviation analyzing system determines (1003), when the respective average chromaticity values of a range (4) of luminance levels indicate—to a predeterminable extent—chromaticity deviations (5) from the respective average chromaticity values (6) of other luminance levels (7), that a black level setting of the image sensor is drifted from a true black level.

Abstract: A method of configuring a camera comprising: collecting a video data with the camera, providing a plurality of imaging profiles, each imaging profile being associated with a set of scene characteristics, for each imaging profile, generating a spatial output data in dependence on the video data and the set of scene characteristics of the imaging profile, wherein the spatial output data is indicative of spatial locations of events detected in the video data matching one or more of the scene characteristics, performing a comparison of the spatial output data of each of the plurality of imaging profiles, selecting a preferred imaging profile in dependence on the comparison, configuring the camera to operate according to the preferred imaging profile.

Abstract: A method for suppressing chromatic aberration, especially blue or red fringing, in a digital image with multiple color channels is disclosed. The method comprises negatively correcting a first color channel by subtracting an overshoot component of the first color channel. The subtraction is subject to a lower threshold, which is dependent on a local value of at least one further color channel.

Abstract: A first image is captured by the camera, using a first focus setting and a first aperture size. A first protrusion focus measure in a protrusion area of an object in the first image and a first recess focus measure in a recess area of the object in the first image are determined. A second image is captured by the camera, using the first focus setting and a second aperture size, and the object is detected. A second protrusion focus measure and a second recess focus measure are determined in the second image. A protrusion focus difference between the first and second protrusion focus measures, and a recess focus difference between the first and second recess focus measures are calculated. The protrusion focus difference and the recess focus difference are compared and if they differ by less than a predetermined threshold amount, it is determined that the object is fake.

Abstract: The present disclosure relates to a method of motion segmentation (100) in a video stream. The method comprises the steps of: acquiring (101) a sequence of image frames; dividing (102) a first frame (401) into a plurality of image blocks (403); comparing (103) each image block (403) against a corresponding reference image block (404) and providing a measure of dissimilarity; for image blocks having a measure of dissimilarity less than a threshold: discarding (104a) the image blocks, and for image blocks having a measure of dissimilarity greater than the threshold: keeping (104b) the image blocks and further dividing the image blocks into a new plurality of image blocks (405); repeating the steps of dividing (102) and comparing (103) until a stop condition is met (105a); generating (106) a motion mask (407) indicating areas of movement (408).

Abstract: The present disclosure relates to a method of motion segmentation (100) in a video stream. The method comprises the steps of: acquiring (101) a sequence of image frames; dividing (102) a first frame (401) into a plurality of image blocks (403); comparing (103) each image block (403) against a corresponding reference image block (404) and providing a measure of dissimilarity; for image blocks having a measure of dissimilarity less than a threshold: discarding (104a) the image blocks, and for image blocks having a measure of dissimilarity greater than the threshold: keeping (104b) the image blocks and further dividing the image blocks into a new plurality of image blocks (405); repeating the steps of dividing (102) and comparing (103) until a stop condition is met (105a); generating (106) a motion mask (407) indicating areas of movement (408).

Abstract: A method of configuring a camera comprising: collecting a video data with the camera, providing a plurality of imaging profiles, each imaging profile being associated with a set of scene characteristics, for each imaging profile, generating a spatial output data in dependence on the video data and the set of scene characteristics of the imaging profile, wherein the spatial output data is indicative of spatial locations of events detected in the video data matching one or more of the scene characteristics, performing a comparison of the spatial output data of each of the plurality of imaging profiles, selecting a preferred imaging profile in dependence on the comparison, configuring the camera to operate according to the preferred imaging profile.

Abstract: A method for determining whether a video camera is out-of-focus comprises: capturing image data; setting a focus setting difference threshold based on a filter function configured to filter the image data; adjusting a focus setting between a present focus setting and an altered focus setting such that a first subset of the image data is captured with the video camera being set in the present focus setting and such that a second subset of the image data is captured with the video camera being set in the altered focus setting, wherein the adjusting is performed such that a difference between the present and altered focus settings is below the threshold; forming the video stream by applying the filter function on the image data; determining first and second focus metrics of the image data; and determining whether the video camera is out-of-focus by comparing the first and second focus metrics.

Abstract: The present disclosure relates to a method performed by a deviation analyzing system (1) for black level drift assessment of a digital camera image sensor (21). The deviation analyzing system measures (1001) for pixels of an image captured by the image sensor, a respective luminance value and corresponding chromaticity value of each pixel. The deviation analyzing system further determines (1002) a respective average chromaticity value for differing luminance levels of the measured luminance values, based on for each luminance level averaging the corresponding measured chromaticity values. Moreover, the deviation analyzing system determines (1003), when the respective average chromaticity values of a range (4) of luminance levels indicate—to a predeterminable extent—chromaticity deviations (5) from the respective average chromaticity values (6) of other luminance levels (7), that a black level setting of the image sensor is drifted from a true black level.

Abstract: A method for determining whether a video camera is out-of-focus comprises: capturing image data; setting a focus setting difference threshold based on a filter function configured to filter the image data; adjusting a focus setting between a present focus setting and an altered focus setting such that a first subset of the image data is captured with the video camera being set in the present focus setting and such that a second subset of the image data is captured with the video camera being set in the altered focus setting, wherein the adjusting is performed such that a difference between the present and altered focus settings is below the threshold; forming the video stream by applying the filter function on the image data; determining first and second focus metrics of the image data; and determining whether the video camera is out-of-focus by comparing the first and second focus metrics.

Abstract: A method of reducing purple fringing in images captured by a camera, comprises: acquiring a raw image of a scene with an image sensor of the camera, demosaicing the raw image, and applying an adjusted color correction matrix to the demosaiced raw image. The adjusted color correction matrix is deduced by calibrating the spectral response of the image sensor to a color rendition chart to which the color data of a purple fringe has been added, and furthermore the color correction matrix is adjusted such that the image sensor response for color values of the purple fringe is transformed into color values of a predetermined replacement color following application of the color correction matrix.

Abstract: A method and a digital video camera for reducing intensity variations in a video stream depicting a scene comprising capturing, using a first sensor setting, a first frame; detecting a change in intensity in a portion of the first frame, the portion represents a first area of the scene; determining a second sensor setting based on the first frame; capturing, using the second sensor setting, a second frame; creating a local tone mapping mask, wherein a local tone mapping in the first area of the scene is different from a local tone mapping in an area outside the first area, and wherein the local tone mapping in the area outside the first area is based on a relation between the first sensor setting and the second sensor setting; and applying the local tone mapping mask to the second frame.

Abstract: A method for determining a local contrast value for a digital image captured by an image sensor in a camera comprising: applying an edge detection algorithm to image data of the digital image, thereby obtaining a data set pertaining to edges in the digital image; calculating, based on said data set, an edge occurrence value for the digital image; estimating, based on image data of the digital image and a noise model of the image sensor, an estimated image sensor noise for the digital image; and computing the local contrast value as a relationship between the edge occurrence value of the digital image and the expected edge occurrence value for the digital image. A method for adjusting a focus setting of a camera using the local contrast value for images captured by the camera.

Abstract: A method and a digital video camera for reducing intensity variations in a video stream depicting a scene comprising capturing, using a first sensor setting, a first frame; detecting a change in intensity in a portion of the first frame, the portion represents a first area of the scene; determining a second sensor setting based on the first frame; capturing, using the second sensor setting, a second frame; creating a local tone mapping mask, wherein a local tone mapping in the first area of the scene is different from a local tone mapping in an area outside the first area, and wherein the local tone mapping in the area outside the first area is based on a relation between the first sensor setting and the second sensor setting; and applying the local tone mapping mask to the second frame.

Abstract: A method of reducing purple fringing in images captured by a camera, comprises: acquiring a raw image of a scene with an image sensor of the camera, demosaicing the raw image, and applying an adjusted color correction matrix to the demosaiced raw image. The adjusted color correction matrix is deduced by calibrating the spectral response of the image sensor to a color rendition chart to which the color data of a purple fringe has been added, and furthermore the color correction matrix is adjusted such that the image sensor response for color values of the purple fringe is transformed into color values of a predetermined replacement color following application of the color correction matrix.

Abstract: A method of reducing purple fringing in images captured by a camera, comprises: acquiring a raw image of a scene with an image sensor of the camera, demosaicing the raw image, and applying an adjusted color correction matrix to the demosaiced raw image. The adjusted color correction matrix is deduced by calibrating the spectral response of the image sensor to a color rendition chart to which the color data of a purple fringe has been added, and furthermore the color correction matrix is adjusted such that the image sensor response for color values of the purple fringe is transformed into color values of a predetermined replacement color following application of the color correction matrix.

Abstract: A method for determining a local contrast value for a digital image captured by an image sensor in a camera comprising: applying an edge detection algorithm to image data of the digital image, thereby obtaining a data set pertaining to edges in the digital image; calculating, based on said data set, an edge occurrence value for the digital image; estimating, based on image data of the digital image and a noise model of the image sensor, an estimated image sensor noise for the digital image; and computing the local contrast value as a relationship between the edge occurrence value of the digital image and the expected edge occurrence value for the digital image. A method for adjusting a focus setting of a camera using the local contrast value for images captured by the camera.

Abstract: A method of reducing purple fringing in images captured by a camera, comprises: acquiring a raw image of a scene with an image sensor of the camera, demosaicing the raw image, and applying an adjusted color correction matrix to the demosaiced raw image. The adjusted color correction matrix is deduced by calibrating the spectral response of the image sensor to a color rendition chart to which the color data of a purple fringe has been added, and furthermore the color correction matrix is adjusted such that the image sensor response for color values of the purple fringe is transformed into color values of a predetermined replacement color following application of the color correction matrix.