Camera Exposure Optimization Using Motion Analysis

Solution Overview

Problem

Existing automatic exposure control systems in digital cameras do not account for camera shake or motion within the scene, leading to potential image blur and suboptimal exposure settings.

Innovation Solution

The system calculates motion quantities from pre-capture images to adjust exposure parameters, minimizing motion blur by optimizing exposure time, aperture, and gain based on detected motion, allowing for better image quality by synchronizing the capture with minimal motion.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If exposure time is increased to improve depth of field and reduce noise, then image quality improves, but motion blur increases due to camera shake and scene motion

Engineering Contradiction:

Improveimage qualityVSAvoidmotion blur

Core Design Contradiction:

Manufacturing precisionVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary analysis of motion quantities from pre-capture images before final image capture, calculating motion vectors and predicting future motion to determine optimal exposure parameters in advance, allowing the camera to capture images at moments of minimal motion blur

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The exposure parameters are made dynamic and adaptive rather than static, continuously adjusting exposure time, aperture, and gain based on real-time motion analysis from pre-capture images and predicted motion trajectories to optimize image quality while minimizing motion blur

Inventive Principle:

Principle #15Dynamics

2Object-affected harmful factors

If exposure time is decreased to reduce motion blur, then motion blur reduces, but depth of field decreases and noise increases

Engineering Contradiction:

Improvemotion blurVSAvoidimage quality

Core Design Contradiction:

Object-affected harmful factorsVSManufacturing precision

Solution Approach 1:

The system performs preliminary analysis of motion quantities from pre-capture images before final image capture, calculating motion vectors and predicting future motion to determine optimal exposure parameters in advance, allowing the camera to capture images at moments of minimal motion blur

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically changes exposure parameters (exposure time, aperture, gain) based on motion analysis to optimize image quality while minimizing motion blur, adjusting multiple parameters simultaneously rather than relying on a single parameter change

Inventive Principle:

Principle #35Parameter changes

3Use of energy by moving object

If aperture is increased to compensate for reduced exposure time, then exposure is maintained, but depth of field is reduced

Engineering Contradiction:

ImproveexposureVSAvoiddepth of field

Core Design Contradiction:

Use of energy by moving objectVSManufacturing precision

Solution Approach 1:

The system dynamically changes exposure parameters (exposure time, aperture, gain) based on motion analysis to optimize image quality while minimizing motion blur, adjusting multiple parameters simultaneously rather than relying on a single parameter change

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS8189057B2Camera exposure optimization techniques that take camera and scene motion into account

Publication Date: 2012.05.29 QUALCOMM INC

AI summary

Quantities of motion regarding an imaging device such as an electronic camera are calculated and used to adjust the exposure time and one or more other exposure parameters used to capture an image to improve the quality of the image. Motion blur caused by movement of the camera or by movement of an object within the scene being photographed is reduced by selecting appropriate exposure parameters. Further, when there is little or no motion detected, the exposure parameters may be selected to improve the depth of field and reduce the noise in the captured image.