Camera Image Fusion for Uniform Focus Across Large-Sensor Frames
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Image capture devices with large sensors and lenses often suffer from non-uniform focus levels across frames due to mismatched ground truth positions, resulting in regions of a frame being out of focus despite autofocus techniques.
Innovation Solution
A camera processor combines frames captured at different focal lengths to generate a composite frame with uniform focus levels by blending regions from each frame using weighting tables, adjusting focal lengths based on depth analysis and lens characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large lenses are used to maximize resolution and light capture, then image quality and pixel density are improved, but non-uniform focus levels occur across the frame due to mismatched ground truth positions
Solution Approach 1:
The image frame is divided into multiple regions (first region and second region) with different focus levels. The processor selectively combines in-focus regions from different frames to create a composite frame with uniform focus across the entire image, resolving the non-uniform focus problem caused by large lenses.
Solution Approach 2:
The patent introduces a temporal dimension by capturing multiple frames at different focal lengths and combining them. This multi-frame approach allows the system to overcome the spatial focus uniformity limitation of large lenses by selecting and merging appropriate regions from different temporal captures.
2Measurement precision
If autofocus techniques are applied, then center region focus is improved, but outer regions remain out of focus due to lens characteristics
Solution Approach 1:
Different regions of the image frame are assigned different focus levels appropriate to their content. The processor identifies which regions are in-focus in each frame and selectively combines them, allowing the center and outer regions to have optimal focus levels from different source frames.
Solution Approach 2:
The frame is segmented into center and outer regions with different focus requirements. By combining in-focus center regions from one frame with in-focus outer regions from another frame, the system achieves uniform focus across all regions despite their different focus characteristics.
3Manufacturing precision
If multiple frames at different focal lengths are captured and combined, then focus uniformity across the composite frame is improved, but processing complexity increases
Solution Approach 1:
The system performs preliminary depth analysis and focus assessment on multiple captured frames before combining them. By pre-identifying in-focus regions and determining the optimal composite frame structure, the processing complexity is managed through organized preliminary steps rather than complex real-time processing.
Solution Approach 2:
The processor automatically analyzes frame focus levels, identifies in-focus regions, and performs the combination operation without external intervention. This self-service approach streamlines the complex multi-frame processing by making the system autonomous in determining and executing the optimal composite frame generation.
Data Source
AI summary
In general, techniques are described regarding fusing or combining frames of image data to generate composite frames of image data. Cameras comprising camera processors configured to perform the techniques are also disclosed. A camera processor may capture multiple frames at various focal lengths. The frames of image data may have various regions of the respective frame in focus, whereas other regions of the respective frame may not be in focus, due to particular configurations of lens and sensor combinations used. The camera processor may combine the frames to achieve a single composite frame having both a first region (e.g., a center region) and a second region (e.g., an outer region) in focus.