Qualcomm incorporated (20240378698). FRAME ENHANCEMENT USING A DIFFUSION MODEL simplified abstract

FRAME ENHANCEMENT USING A DIFFUSION MODEL

Organization Name

qualcomm incorporated

Inventor(s)

Jens Petersen of Amsterdam (NL)

Michal Jakub Stypulkowski of Wroclaw (PL)

Noor Fathima Khanum Mohamed Ghouse of Amsterdam (NL)

Auke Joris Wiggers of Amsterdam (NL)

Guillaume Konrad Sautiere of Amsterdam (NL)

FRAME ENHANCEMENT USING A DIFFUSION MODEL - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240378698 titled 'FRAME ENHANCEMENT USING A DIFFUSION MODEL

Simplified Explanation: The patent application describes a system for processing image data, where a computing device determines optical flow between frames of different resolutions and uses a diffusion machine learning model to generate an output frame.

• Key Features and Innovation:

   - Determination of optical flow between frames of different resolutions.
   - Warping of frames to generate higher resolution output.
   - Utilization of a diffusion machine learning model for processing image data.

• Potential Applications:

   - Video processing and enhancement.
   - Image stabilization in photography and videography.
   - Augmented reality applications.

• Problems Solved:

   - Enhancing image quality by generating higher resolution frames.
   - Improving image processing efficiency.
   - Addressing challenges in optical flow estimation.

• Benefits:

   - Enhanced visual quality in image and video processing.
   - Increased accuracy in optical flow estimation.
   - Improved performance in image enhancement tasks.

• Commercial Applications:

   - Video editing software development.
   - Surveillance systems with improved image processing capabilities.
   - Virtual reality content creation tools.

• Prior Art:

   - Prior research on optical flow estimation techniques.
   - Existing machine learning models for image processing.

• Frequently Updated Research:

   - Ongoing advancements in optical flow estimation algorithms.
   - Latest developments in machine learning models for image processing.

Questions about Image Processing Technology: 1. How does the diffusion machine learning model improve image processing tasks? 2. What are the potential limitations of using optical flow estimation in image data processing?

Original Abstract Submitted

systems and techniques are provided for processing image data. according to some aspects, a computing device can determine an optical flow between a current frame having a first resolution and a first previous frame having the first resolution. the computing device can warp a second previous frame having a second resolution based on the determined optical flow to generate a warped previous frame having the second resolution, the second resolution being higher than the first resolution. the computing device can process, using a diffusion machine learning model, a noise frame, the current frame, and the warped previous frame to generate an output frame having the second resolution.