Update Fixed Pattern Noise Matrix

A fixed pattern noise, matrix technology, used in image enhancement, instrumentation, television, etc., to solve problems such as inappropriate calibration of image sensors

Active Publication Date: 2022-06-21
AXIS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, even if the position of the fixed-pattern noise relative to the image sensor is fixed, the signal strength of the noise will vary over time
Therefore, the calibration of image sensors to remove fixed pattern noise is also inappropriate

Method used

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Examples

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Embodiment Construction

[0062] The inventive concept will now be described more fully hereinafter with reference to the accompanying drawings that illustrate currently preferred variations of the inventive concept. The inventive concepts, however, may be embodied in many different forms and should not be construed as limited to the variants set forth herein; rather, these variants are provided so that they will be thorough and complete, and will fully convey the scope of the inventive concepts to those skilled in the art scope.

[0063] figure 1 A camera 1100 is shown. Camera 1100 includes an image sensor 1102 configured to capture a video stream. Camera 1100 may be a thermal camera. Image sensor 1102 may be sensitive to infrared light.

[0064] Camera 1100 further includes motion sensor 1104 . The motion sensor 1104 may include a gyroscope, an accelerometer, and / or a three-axis compass. Motion sensor 1104 may determine data related to vibration and / or movement of image sensor 1102 .

[0065] ...

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Abstract

The present invention relates to updating a fixed pattern noise matrix. A method for updating a fixed pattern noise matrix, comprising: calculating a first difference between a target image and a first different image in an electronic image stabilized video stream, thereby obtaining a first difference matrix; calculating the electronic image stabilized A second difference between the target image and a second different image in the optimized video stream to obtain a second difference matrix; a set of candidate positions for fixed pattern noise is identified by locating the first difference in the first difference matrix set position; locate the second set of positions in the second difference matrix; find a set of overlapping positions between the first set of positions and the second set of positions, and adjust the set of overlapping positions based on the stabilization data of the target image, wherein adjusting The subsequent set of overlapping positions is used as the set of candidate positions for fixed pattern noise; and, for each position in the set of candidate positions in the fixed pattern noise matrix, the fixed pattern noise value at that position is updated.

Description

technical field [0001] The present invention relates to a method and camera for updating a fixed pattern noise matrix and a method for processing image data. Background technique [0002] In an image, there are often different types of image noise that affect the image quality and thus any analysis performed on the image. Typically, the location of noise in an image can be random or fixed. Due to its random nature, random noise can be reduced by, for example, averaging multiple images. Fixed noise, commonly referred to as fixed pattern noise, is a type of noise that varies from image sensor to image sensor and can be, for example, by variants related to the properties of each pixel in the image sensor or by in a readout circuit, to name a few. A type of noise caused by variants of . Therefore, the location of fixed pattern noise in an image is related to the location of the pixel in the image sensor itself. Therefore, it is not appropriate to reduce the fixed pattern noi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N5/365
CPCH04N25/67H04N25/674G06T5/002G06T5/50G06T2207/10016G06T2207/10048H04N23/80H04N23/683H04N23/6812
Inventor 托马斯·温泽尔耶斯佩尔·本特松
Owner AXIS
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