Motion Vector Detection Using Downsampled Image Metadata
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Solution Overview
Problem
High-definition image capturing apparatuses face challenges in accurately detecting motion vectors due to increased pixel count, leading to higher circuit scale and power consumption, particularly when transitioning from full HD to 4K or 8K resolutions.
Innovation Solution
The implementation of an image processing apparatus that performs motion vector detection using reduced or thinned image signals during capture and utilizes metadata to determine detection areas during playback, allowing for accurate motion vector detection without significant increases in circuit scale.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion vector detection is performed using full-resolution images (e.g., 4K or 8K), then motion vector detection accuracy is improved, but circuit scale and power consumption increase significantly
Solution Approach 1:
The patent divides the image processing into two stages: first performing motion vector detection on a downsampled version of the image to obtain initial motion vector information, then using this information to guide selective processing of the full-resolution image. This segmentation allows the system to benefit from both low-resolution speed and high-resolution accuracy without paying the full cost of processing the entire high-resolution image.
Solution Approach 2:
The patent performs motion vector detection on only a portion of the full-resolution image data by first processing a downsampled version. Instead of processing all pixels at full resolution, the system processes a subset (the downsampled image) to obtain motion information, then applies this to the full-resolution data. This partial action approach achieves high accuracy without the computational burden of complete full-resolution processing.
2Measurement precision
If motion vector detection is performed on full-resolution images, then detection accuracy is improved, but power consumption increases
Solution Approach 1:
The patent segments the computationally intensive motion vector detection task into two parts: an initial detection phase using downsampled images that consumes less power, and a refinement phase using full-resolution images guided by the initial results. This segmentation reduces overall power consumption while maintaining detection accuracy.
Solution Approach 2:
The system performs partial processing on full-resolution images by first detecting motion vectors on downsampled images and then applying this information to guide processing of the full-resolution data. This partial action approach achieves high detection accuracy without consuming the excessive power that would be required for complete full-resolution processing.
3Manufacturing precision
If the image size is increased from full HD to 4K or 8K, then image quality is improved, but the number of pixels and processing load increase four times or sixteen times
Solution Approach 1:
The patent segments the image data into two representations: a downsampled version for efficient motion analysis and the full-resolution version for final output. This allows the system to process 4K or 8K images by performing motion detection on a smaller downsampled version, thereby maintaining image quality while improving processing efficiency.
Solution Approach 2:
The system performs motion vector detection on a partial representation (downsampled image) rather than the complete full-resolution image. This partial processing approach reduces the processing load from four times or sixteen times to a much lower level, while still enabling high-quality output by applying the motion information to the full-resolution data.
Data Source
AI summary
An image processing apparatus comprises a motion vector detection unit, a generation unit for generating information regarding the motion vector as metadata, a recording unit for recording each frame image in association with the metadata; and a control unit for causing the motion vector detection unit to perform motion vector detection by using an image signal on which reduction processing or thinning processing was performed, and causing the motion vector detection unit to determine an image area based on the metadata and to perform motion vector detection by using an image signal on which reduction processing or thinning processing was not performed or on which reduction processing was performed using a smaller reduction ratio than that used during the image capturing operation or thinning processing was performed using a smaller thinning ratio than that used during the image capturing operation.