17955846. DEVICE AND METHOD FOR IMAGE PROCESSING simplified abstract (HUAWEI TECHNOLOGIES CO., LTD.)

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DEVICE AND METHOD FOR IMAGE PROCESSING

Organization Name

HUAWEI TECHNOLOGIES CO., LTD.

Inventor(s)

Zeju Li of Shenzhen (CN)

Liang Chen of Shenzhen (CN)

Gregory Slabaugh of London (GB)

Liu Liu of Beijing (CN)

Zhongqian Fu of Beijing (CN)

DEVICE AND METHOD FOR IMAGE PROCESSING - A simplified explanation of the abstract

This abstract first appeared for US patent application 17955846 titled 'DEVICE AND METHOD FOR IMAGE PROCESSING

Simplified Explanation

The patent application describes a device that includes an image processor capable of implementing two machine learning models. The first model is used for restoring degraded image data, while the second model is used for identifying areas of an image that require special attention during the restoration process. The output of the second model is then used as input to the first model to optimize the restoration process.

  • The device includes an image processor.
  • The image processor implements two machine learning models.
  • The first model is used for restoring degraded image data.
  • The second model is used for identifying areas of an image that require processing emphasis during restoration.
  • The output of the second model is used as input to the first model to optimize the restoration process.

Potential Applications

  • Image restoration and enhancement in various fields such as photography, medical imaging, and surveillance.
  • Improving the quality of degraded images in historical archives or damaged photographs.
  • Enhancing the visibility of important details in low-quality or blurry images.

Problems Solved

  • Restoring degraded image data often requires manual intervention or trial-and-error approaches.
  • Identifying areas of an image that need special attention during restoration can be time-consuming and subjective.
  • Optimizing the restoration process based on the specific needs of different images can be challenging.

Benefits

  • Automation of the image restoration process, reducing the need for manual intervention.
  • Improved accuracy and efficiency in identifying areas of an image that require processing emphasis.
  • Optimization of the restoration process based on the specific needs of each image, resulting in enhanced image quality.


Original Abstract Submitted

A device comprising an image processor, the image processor being configured to implement: a first machine learning model for performing restoration processing on degraded image data; and a second machine learning model for recognizing areas of an image requiring processing emphasis during the restoration processing; wherein the output of the second machine learning model is an input to the first machine learning model to optimize the restoration processing.

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