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  6. Demosaicing using machine learning "AIRD"

Demosaicing using machine learning "AIRD"

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last updated:Aug 02, 2020

リアロップ 本社
リアロップ 本社
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No more zipper noise! Super-resolution RAW development technology that removes optical LPF and diffraction blur.

"AIRD (Artificial Intelligence Retina Development, formerly Phase Shift Development)" is a super-resolution RAW development technology using machine learning. It is well-suited for RAW development for Optical Learning. It eliminates zipper noise and removes blur caused by optical LPF and diffraction. Additionally, it prevents the occurrence of color artifacts, improves the resolution of red, blue, green, and monochrome, and reduces jaggies. 【Features】 ■ Well-suited for RAW development for Optical Learning ■ Removes blur caused by optical LPF and diffraction ■ Reduces sensor noise ■ Suppresses the emphasis on demosaicing degradation *For more details, please refer to the PDF document or feel free to contact us.

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aird_concept.png

Demosaicing using machine learning "AIRD"

aird_concept.png
aird_concept.png
  • Related Link - https://realop.co.jp/technology.html#artificial_in…

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【Other Machine Learning Algorithms】 ■Keep Resolution Mapping(TM): Geometric transformation using machine learning (such as trapezoidal correction) ■Super Resolution Stepless Zoom(TM): Continuously variable zoom using machine learning *For more details, please refer to the PDF document or feel free to contact us.

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Detailed information

  • aird_dlmmse.png

    This is the RAW development result using conventional high-performance demosaicing (DLMMSE). It can be seen that zipper noise is occurring.

  • aird_aird.png

    This is the RAW development result by AIRD (Artificial Intelligence Retina Development). You can see that the zipper noise has been eliminated.

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Demosaicing using machine learning "AIRD"

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Realop Co., Ltd. provides image processing-related intellectual property rights licensing (such as our Optical Learning® technology), software development and sales, and technical consulting services to offer differentiated image processing technologies to our partner companies, supporting their revenue growth by enhancing their product capabilities. With years of experience, we develop learning-based super-resolution algorithms that take into account the characteristics of hardware and GPUs, so please feel free to contact us if you have any requests.

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