Image Processing Apparatus Using Metadata for Intentional Blur Control
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Solution Overview
Problem
Existing image processing systems lack the ability to perform optimal image quality processing based on producer intention due to insufficient metadata information, particularly struggling with blur and noise types such as camera motion blur, film scanner jitter, film grain noise, and breathing noise, which affect high-definition image content like 4K images.
Innovation Solution
An image processing apparatus and method that utilize metadata with flag information and image processing information to determine and apply specific processing techniques for each frame, including sharpness enhancement, noise processing, brightness adjustment, and color correction, allowing for intentional preservation or removal of certain effects based on producer intent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image processing is performed to remove all blur and noise, then image quality improves, but intentional artistic effects (camera motion blur, film grain noise) are lost
Solution Approach 1:
The patent applies different processing strategies to different types of blur and noise based on their characteristics and intent. Motion blur is preserved when intentional but removed when due to camera shake, while film grain noise is preserved as an artistic effect but other noise types are removed. This local differentiation resolves the contradiction by treating similar phenomena differently based on their specific nature.
Solution Approach 2:
The system uses metadata feedback from the content provider to guide processing decisions. The metadata indicates whether blur or noise is intentional, allowing the processor to make informed decisions about whether to remove these artifacts. This feedback mechanism resolves the contradiction by providing the information needed to distinguish between harmful and beneficial effects.
2Manufacturing precision
If comprehensive image processing is applied to all frames, then image quality improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis of each frame to identify the type of blur or noise present before applying processing. By detecting motion blur, film grain noise, or other artifacts in advance, the system can selectively apply processing only when needed, avoiding unnecessary computation on frames that don't require enhancement. This preliminary detection resolves the contradiction by enabling selective processing based on actual needs.
3Measurement precision
If metadata includes detailed processing information, then processing accuracy improves, but data transmission and storage requirements increase
Solution Approach 1:
The patent extracts only the essential processing information needed for quality enhancement into the metadata, rather than including all possible processing parameters. The metadata contains specific indicators for motion blur presence, film grain noise characteristics, and other key features, allowing accurate processing decisions with minimal data overhead. This selective extraction resolves the contradiction by providing sufficient information for accurate processing without excessive data volume.
Data Source
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AI summary
An image processing method, including: receiving image content and metadata of the image content, the metadata content comprising flag information indicating whether to perform image processing on the image content and image processing information; determining whether to perform the image processing for each frame based on the flag information; performing, in response to determining to perform the image processing for an image frame, the image processing based on the image processing information on the image frame; and outputting the image processed image frame on which the image processing is performed.