Axis Ab

Björn Benderius

Niclas Svensson

Johan Jeppsson

Viktor Edpalm

Xing Danielsson Fan

Fredrik Pihl

Jimmie Jönsson

Anton Öhrn

Dennis Nilsson

Henrik Eliasson

Andreas Muhrbeck

Johan Nyström

Johan Nystrom

Gunnar Dahlgren

Johan Jeppsson Karlin

Sebastian Fors

Stefan Lindgren

Fritjof Jonsson

Karin Dammer

Jonas Levin

Karlin Johan Jeppsson

Johan NYSTRÖM

A method for stray light compensation is disclosed. The method comprising: acquiring a first image with a first imaging device covering a first field-of-view; acquiring a second image with a second imaging device covering a second field-of-view, wherein the second field-of-view is larger than the first field-of-view and wherein the first field-of-view is included in the second field-of-view; estimating stray light components in pixels of the first image from pixel data of pixels in the second image; and compensating for stray light in the first image by subtracting the estimated stray light components in pixels of the first image. Also, a system for stray light compensation is disclosed.

Method and system for stray light compensation

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.

Method of configuring a camera

Systems and methods are disclosed for inter-coding of a video. To inter-code a frame relative to a previous frame of the video, techniques disclosed include partitioning the frame and the previous frame into corresponding portions. Then, for each portion of the frame, a difference between the frame's portion and its corresponding portion in the previous frame is determined. A probability for suppressing the determined difference is further devised as a function of the difference. A decision whether to suppress the difference is then made based on the probability. If a decision to suppress has been made, the difference between the frame portion and the corresponding portion in the previous frame is suppressed before the frame portion is inter-encoded relative to the corresponding portion in the previous frame.

Encoding of a video sequence

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.

Determining whether a camera is out-of-focus

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.

Method for reducing intensity variations in a video image stream depicting a scene

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.

Determination of a contrast value for a digital image

A method for controlling a video camera which is configured to capture and process image frames prior to encoding. The method comprises determining whether the video camera is going to encode an image frame as an intra-frame or an inter-frame. If the image frame is going to be encoded as an inter-frame, the video camera is controlled to capture and process the image frame using first settings prior to encoding. If the image frame is going to be encoded as an intra-frame, the video camera is controlled to capture and process the image frame using second settings prior to encoding, wherein the second settings are modified in relation to the first settings to further reduce a level of noise in the image frame.

Controller, video camera, and method for controlling a video camera

A method of encoding a video stream comprising receiving a frame of a video stream to be encoded, performing motion detection in the frame to identify steady regions, and temporally filtering the frame so as to provide temporally filtered pixel values. For a pixel in the steady regions of the frame, the temporally filtered pixel value is used when encoding the pixel, on a condition that the pixel belongs to a block of pixels of the frame that will be intra-coded. On a condition that the pixel instead belongs to a block of pixels of the frame that will be inter-coded, a value that was used when encoding a corresponding pixel of the immediately preceding frame is used when encoding the pixel.

Method, a video encoder, and a video camera for encoding a video stream

The present invention relates generally to auto focus algorithms for setting a focus of a camera. More specifically, the present invention relates to a method () and device for setting a focus of a camera wherein a camera motion level of the camera is continuously measured (S) during the read-out of pixel data by a rolling shutter image sensor and wherein the auto focus algorithm uses weighted focus measures which are calculated (S) using the continuously measured camera motion levels.

Method and device for setting a focus of a camera

A device and method for determining exposure settings in a camera is disclosed. The method comprises capturing an image frame using an image sensor, the exposure of the capturing is based on an initial exposure value setting, determining a temporary exposure value by finding an exposure value that results in a substantially optimum value when applied to a total cost calculation, calculating a saturated pixels cost related to the saturated pixels for the captured image at the temporary exposure value, determining a next exposure value by finding a decrease in exposure value, in relation to the temporary exposure value, for which decrease a change in total cost for non-saturated pixels, in relation to the total cost for non-saturated pixels at the temporary exposure value, is substantially equal to the saturated pixel cost calculated at the temporary exposure value, using this determined next exposure value for capturing a new image frame.

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Lund, Sweden

Björn Benderius