{"id":1906,"date":"2017-10-13T22:44:52","date_gmt":"2017-10-13T20:44:52","guid":{"rendered":"https:\/\/www.adimec.com\/defect-pixel-correction-even-more-critical-for-high-resolution-machine-vision-cameras\/"},"modified":"2018-07-30T11:48:41","modified_gmt":"2018-07-30T09:48:41","slug":"defect-pixel-correction-even-more-critical-for-high-resolution-machine-vision-cameras","status":"publish","type":"post","link":"https:\/\/www.adimec.com\/ja\/defect-pixel-correction-even-more-critical-for-high-resolution-machine-vision-cameras\/","title":{"rendered":"Defect Pixel Correction Even More Critical for High-Resolution Machine Vision Cameras"},"content":{"rendered":"
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When there are pixels on the image sensor whose response is an extreme outlier, these defect pixels can be corrected to ensure that they do not affect the precision or accuracy of the system.<\/b><\/p>\n

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With the introduction of large CMOS image sensors<\/a> and cameras on the market the topic of defect pixel correction is becoming more important. With more than 25 million pixels or even 1 million pixels on an image sensor, not every single pixel can perform perfectly.  Inspection and measurement systems require uniform, undistorted, consistent images despite imperfect components.  There are several techniques for camera manufacturers to achieve this, and sometimes there are pixels whose response differs so significantly from the mean response of all of the other pixels that they need to be excluded entirely.  These pixels are referred to as defect or defective pixels.<\/p>\n

There are 2 types of defect pixels:<\/p>\n

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  1. Hot pixels:  Pixels with an extremely large offset for example due to excessive dark current (local impurities\/lattice defects).<\/li>\n
  2. Dead pixels:  pixels with much lower sensitivity<\/li>\n