Super-Resolution Image Enhancement via Sub-Pixel Motion Alignment
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Solution Overview
Problem
Current super-resolution image processing techniques are computationally intensive and often limited in generating higher resolution images from multiple lower resolution images, particularly in applications like medical imaging, face recognition, and satellite imaging, where efficient image enhancement is crucial.
Innovation Solution
A method for generating an enhanced image of a predetermined scene by configuring a computing device to continuously capture images while estimating and achieving a target resolution, using sub-pixel motion vectors to align and combine images, and performing interpolation to fill empty pixel locations, thereby increasing the image resolution without continuous capture when motion is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If super-resolution image processing is applied to generate higher resolution images from multiple lower resolution images, then image resolution and detail are improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The system performs preliminary actions by continuously capturing multiple images at lower resolution before the final enhancement step. These pre-captured images are stored and prepared in advance, allowing the computationally intensive super-resolution processing to work with pre-organized data rather than processing images in real-time, thus reducing the actual processing complexity when enhancement is needed.
Solution Approach 2:
The super-resolution process is segmented into distinct phases: image capture phase (continuous low-resolution capture), alignment phase (using sub-pixel motion vectors), and enhancement phase (interpolation and combining). This segmentation allows the system to distribute computational load across different time periods and optimize each phase independently, reducing the peak computational complexity.
2Loss of information
If multiple lower resolution images are captured and combined to generate an enhanced image, then image detail and resolution are improved, but processing time and computational resources increase
Solution Approach 1:
The system maintains continuous useful action by continuously capturing images during the predetermined period without interruption. This continuous capture ensures that sufficient image data is accumulated to achieve the target resolution enhancement, while the automated processing pipeline ensures that the time from capture to enhancement is minimized, balancing information quality with processing efficiency.
Solution Approach 2:
The patent replaces traditional mechanical or manual image processing methods with automated computational algorithms. Specifically, sub-pixel motion vector estimation and interpolation algorithms automatically align and combine images without manual intervention, significantly reducing processing time while maintaining or improving image detail compared to manual methods.
3Measurement precision
If continuous image capture is performed to achieve target resolution, then image quality and resolution are improved, but energy consumption and capture duration increase
Solution Approach 1:
The system implements periodic action by capturing images continuously only during a predetermined period when enhancement is needed, rather than continuously indefinitely. The capture operation is periodic and time-bound, allowing the system to accumulate sufficient images for resolution enhancement while consuming energy only during necessary capture intervals, not continuously.
Solution Approach 2:
The system applies partial action by capturing more images than the absolute minimum needed for enhancement during the predetermined period. This excessive capture ensures that sufficient data is available to achieve the target resolution even if some images are discarded due to motion or quality issues, while still limiting total energy consumption by confining capture to a specific time window rather than indefinite continuous capture.
Data Source
AI summary
A method, device, system, and article of manufacture are provided for generating an enhanced image of a predetermined scene from images. In one embodiment, a method comprises receiving, by a computing device, a first indication associated with continuous image capture of a predetermined scene being enabled; in response to the continuous image capture being enabled, receiving, by the computing device, from an image sensor, a reference image and a first image, wherein each of the reference image and the first image is of the predetermined scene and has a first resolution; determining an estimated second resolution of an enhanced image of the predetermined scene using the reference image and the first image; and in response to the continuous image capture being disabled determining the enhanced image using the reference image and the first image, wherein the enhanced image has a second resolution that is at least the first resolution and about the estimated second resolution.