Super Resolution Interpolation for Digital Camera Zoom
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Solution Overview
Problem
Digital zoom systems in digital cameras introduce significant image aberrations such as aliasing, blurring, and haloing, which are not present in optical zoom systems.
Innovation Solution
A multiple-frame based super resolution interpolation method that increases the resolution of input frames through interpolation and merging, using a set of weights calculated based on motion information, Bayer-pattern configuration, and detail level estimation to minimize aberrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of moving object
If digital zoom systems are used to increase image resolution through image processing techniques, then the field of view is narrowed and image magnification is achieved, but significant image aberrations such as aliasing, blurring, and haloing are introduced
Solution Approach 1:
The patent merges multiple input frames captured at different times to create a single high-resolution output frame. By combining information from multiple frames through interpolation and weighted merging, the system achieves digital zoom magnification while reducing image aberrations that would occur with traditional single-frame digital zoom methods
Solution Approach 2:
The system performs preliminary motion registration and interpolation on multiple input frames before final merging. By pre-processing the frames to account for motion and calculate appropriate weights, the system prepares the data in advance to minimize aberrations during the final image composition
2Manufacturing precision
If multiple input frames are processed through interpolation and merging, then the resolution of digitally zoomed images is increased and noise is reduced, but processing complexity and computational requirements increase
Solution Approach 1:
The patent applies local quality by calculating different weights for different regions and pixels within the image based on motion information and detail level estimation. This allows the system to focus computational resources on areas that benefit most from multiple-frame processing while simplifying processing in less critical regions
Solution Approach 2:
The system dynamically adjusts processing parameters including interpolation methods, weight calculations, and merging strategies based on detected motion and detail levels in the input frames. This adaptive approach optimizes processing complexity by applying more intensive processing only when and where it is most beneficial
Data Source
AI summary
A digital camera system for super resolution image processing constructed to receive a plurality of input frames and output at least one digitally zoomed frame is provided. The digital camera system includes a motion registration module configured to generate motion information associated with the plurality of input frames, an interpolation module configured to generate a plurality of interpolated input frames based at least in part on the plurality of input frames and the motion information, a weights calculation module configured to calculate one or more weights associated with the plurality of input frames based on at least the motion information, and a weighted merging module configured to merge the plurality interpolated input frames consistent with the one or more weights to generate the at least one digitally zoomed frame.