Burst Mode Image Selection Using Intrinsic Quality Metrics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Digital cameras face challenges in automatically selecting an optimum image from a burst mode sequence without user intervention, as existing methods often require external references or manual selection processes.
Innovation Solution
The camera sets different combinations of exposure duration and white balance settings to capture multiple frames, extracts image metrics such as edge count, luma level, color cast distance, and smoothness, and selects the frame with the highest score based on these parameters, ensuring an optimal image is chosen automatically without external references.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automatic image selection is implemented without external references, then ease of operation is improved, but measurement precision may deteriorate
Solution Approach 1:
The system performs self-service by automatically selecting the optimal image from burst mode captures using intrinsic image quality metrics without requiring external reference images or manual user intervention. The image processor autonomously evaluates multiple captured frames and selects the best one based on computed quality parameters.
Solution Approach 2:
The patent replaces manual mechanical selection (user viewing and choosing images) with an automated computational system that uses image quality metrics and algorithms to objectively select the optimal image, substituting human judgment with automated measurement and evaluation.
2Manufacturing precision
If multiple image parameters are evaluated, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The image quality evaluation is segmented into distinct independent parameters including edge count, luma level, color cast distance, and smoothness. Each parameter is computed separately using dedicated algorithms, allowing the system to evaluate multiple aspects of image quality without requiring a single complex evaluation mechanism.
Solution Approach 2:
The system changes and evaluates multiple image parameters simultaneously (edge count, luma level, color cast distance, smoothness) rather than relying on a single quality metric. This multi-parameter approach enables comprehensive image quality assessment while using straightforward computational methods for each parameter.
Data Source
AI summary
An aspect of the present invention selects one of the images captured in burst mode as an optimum image based on processing only the captured images, without requiring any external images. According to another aspect of the present invention, the camera settings are set to different combination of values and a frame is formed for each combination of values from the corresponding captured image. Image metrics representing inherent image qualities may be extracted from each of the frames and one of the frames is selected based on the extracted metrics. In an embodiment, each combination of the camera settings includes corresponding values for exposure duration and white balance.