Multi-Parameter Image Capture for High Dynamic Range and Depth of Field
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Solution Overview
Problem
Conventional camera automatic modes often produce suboptimal images due to limitations in optics and sensor capabilities, such as limited depth of field, dynamic range, and noise in low light conditions, and fail to capture scenes accurately, especially in high dynamic range scenarios, and do not allow for re-experiencing the scene under different conditions.
Innovation Solution
A method and system that automatically determine image acquisition settings to capture multiple images, which are then combined to create a 'perfect' shot with extended bit-depth and layered focus representation, allowing for improved fidelity and adaptability to different scene conditions without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional automatic mode is used to capture images, then the camera operates automatically without user intervention, but the images produced are suboptimal due to limited depth of field and dynamic range
Solution Approach 1:
The patent segments the image capture process into multiple separate captures with different parameters (focus distance, exposure, aperture) and then combines them computationally. This allows each individual capture to be optimized for a specific condition while the final composite image achieves superior overall quality that cannot be obtained in a single automatic capture.
Solution Approach 2:
The system dynamically changes multiple capture parameters including focus distance, exposure time, and aperture settings across different captures. By varying these parameters and combining the results, the system overcomes the limitations of fixed automatic mode parameters and produces images with extended dynamic range and improved focus accuracy.
2Manufacturing precision
If multiple images are captured with different parameters, then image quality improves, but the system complexity increases
Solution Approach 1:
The system automatically determines which parameter combinations to use and performs the computational merging without requiring user intervention. The camera self-manages the complex multi-parameter capture process and post-processing, eliminating the need for manual mode selection while maintaining high image quality.
Solution Approach 2:
The system uses scene analysis to automatically adjust capture parameters based on detected conditions such as depth of field requirements, dynamic range needs, and focus distance. This feedback-driven approach allows the system to adapt to different scenes automatically, reducing the apparent complexity from the user perspective while maintaining high image quality.
3Device complexity
If a single image is captured, then the capture process is simple, but the scene cannot be re-experienced under different conditions
Solution Approach 1:
The patent captures multiple separate images with different parameters (focus distances, exposure settings) and stores them as distinct data layers. This segmentation allows the scene to be re-experienced by selectively combining different parameter sets, enabling users to view the same scene under different focus conditions, exposure levels, and other parameter variations.
Solution Approach 2:
The system adds multiple dimensions of parameter variation to the traditional single image capture. By capturing images at different focus distances, exposure times, and aperture settings, the system creates a multi-dimensional representation of the scene that can be explored and re-experienced in various ways without requiring physical repositioning or recapture.
4Object-affected harmful factors
If exposure time is minimized to avoid motion blur in low light, then motion blur is reduced, but noise dominates the captured image
Solution Approach 1:
The system segments the low-light capture into multiple separate images taken at different exposure times. Some images are captured with longer exposure times to gather sufficient light and reduce noise, while others use shorter exposures to minimize motion blur. The computational combination of these segmented captures allows the system to achieve both low noise and minimal motion blur in the final image.
Solution Approach 2:
The patent merges multiple captured images with different exposure parameters into a single final image. By combining images taken at varying exposure times, the system can achieve the optimal balance between noise reduction (from longer exposures) and motion blur minimization (from shorter exposures), something impossible to achieve in a single capture.
Data Source
AI summary
An image processing apparatus, system, and method to automatically determine a plurality of image acquisition settings for an scene; acquire a set of images of the scene, the set of images including multiple images acquired with a distinct plurality of the determined image acquisition settings; and generate a single image by combining the acquired set of images.