Motion-Triggered Image Stabilization for Sharp Frames
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Solution Overview
Problem
Existing camera systems fail to automatically reduce motion blur in images captured in fast-moving environments, such as those involving infants, children, parties, and sports events, due to inability to estimate motion in the scene, leading to blurry images, especially in low-light conditions.
Innovation Solution
A method and apparatus for motion-triggered image stabilization that computes block projection vectors, performs motion estimation using temporal IIR filtering, and adjusts exposure time and gain based on the motion to minimize blur, utilizing a smart ISO algorithm that optimizes exposure time and ISO gain based on the speed of moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If exposure time is optimized for scene brightness, then image brightness is improved, but motion blur increases in fast-moving environments
Solution Approach 1:
The system dynamically adjusts exposure time based on detected motion in the scene. When motion is detected, the exposure time is reduced to freeze motion and prevent blur. When no motion is detected, the exposure time is optimized for brightness. This dynamic adaptation resolves the contradiction between brightness optimization and motion blur prevention.
Solution Approach 2:
The system uses motion detection feedback to control exposure time settings. The motion detection module continuously monitors the scene and provides feedback to the exposure control module, which adjusts exposure parameters accordingly. This closed-loop feedback mechanism enables the system to automatically adapt to moving subjects without manual intervention.
2Illumination intensity
If gain is increased to compensate for low light, then image brightness is improved, but noise and blur increase
Solution Approach 1:
The system dynamically adjusts gain based on motion detection results. When motion is detected, the system prioritizes freezing motion by reducing exposure time rather than increasing gain, thereby avoiding the noise and blur that result from high gain amplification. This dynamic control strategy resolves the contradiction between brightness and image quality.
3Manufacturing precision
If manual sports mode is selected, then motion blur is reduced, but ease of operation deteriorates due to manual selection requirement
Solution Approach 1:
The system performs automatic motion detection and automatically adjusts exposure parameters without requiring manual user input. The camera serves itself by detecting motion in the scene and autonomously optimizing exposure settings to freeze motion. This eliminates the need for manual sports mode selection while maintaining image sharpness.
Solution Approach 2:
The system uses automatic feedback from motion detection to control exposure settings. The motion detection module continuously monitors the scene and provides real-time feedback to adjust exposure time and gain automatically. This automated feedback loop replaces manual mode selection, improving ease of operation while maintaining image quality.
4Manufacturing precision
If exposure time is reduced to freeze motion, then motion blur is reduced, but image brightness deteriorates
Solution Approach 1:
The system changes exposure parameters (time and gain) based on motion detection results. When motion is detected, the system reduces exposure time to freeze motion while carefully managing gain adjustments to maintain acceptable brightness. This parameter optimization resolves the contradiction between sharpness and brightness by finding the optimal balance point.
Data Source
AI summary
A method and apparatus motion triggered image stabilization. The method includes computing projection vector for at least a portion of a frame of an image using horizontal and vertical sums, performing motion estimation utilizing projection vector with the shift of the projection vector from a previous frame, performing temporal IIR filter on the motion vector, calculating the maximum horizontal and vertical motion vectors, obtaining exposure time based on the horizontal and vertical motion vectors and the gain, returning the exposure time and the gain to the auto-exposure, utilizing the returned exposure time and gain, and producing a frame with less motion blur.