Dynamic Image Sensor Configuration for Low-Light Video Stability
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Solution Overview
Problem
Image capture devices struggle with low light conditions and video judder artifacts due to limited frame duration at high frame rates, leading to reduced image quality and increased motion blur.
Innovation Solution
Implementing a dynamic image sensor configuration that reduces frame rate and applies frame rate conversion (FRC) based on motion and scene conditions to enhance signal-to-noise ratio and reduce video judder artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If frame rate is reduced to extend frame duration, then image quality in low light conditions is improved, but video judder artifacts increase
Solution Approach 1:
The system dynamically adjusts the frame rate based on motion detection. When motion is detected, the frame rate is reduced to extend frame duration for better low light performance. When motion is minimal, the frame rate is increased to prevent video judder artifacts. This dynamic adaptation allows the system to optimize between the two competing requirements in real-time.
Solution Approach 2:
The system changes the frame rate parameter based on scene conditions. By detecting motion and adjusting the frame rate accordingly, the system can extend frame duration when needed for low light improvement while maintaining smooth video playback when motion is minimal, thus resolving the contradiction between image quality and video smoothness.
2Measurement precision
If frame rate is reduced to extend frame duration, then signal-to-noise ratio is improved, but motion blur increases
Solution Approach 1:
The system dynamically adjusts frame rate based on motion detection. When the device is detected to be moving or when scene motion is present, the frame rate is reduced to extend frame duration for better signal-to-noise ratio. When motion is minimal, the frame rate is increased to minimize motion blur. This dynamic control allows optimization of SNR without excessive motion blur.
Solution Approach 2:
The system uses motion detection feedback to control frame rate adjustment. By continuously monitoring motion and adjusting frame rate accordingly, the system can extend frame duration to improve signal-to-noise ratio when motion is present, while avoiding excessive motion blur by adapting to actual motion conditions.
3Stability of the object's composition
If frame rate is increased to reduce video judder, then video smoothness is improved, but frame duration is reduced
Solution Approach 1:
The system dynamically adjusts frame rate based on motion detection. When motion is detected, the frame rate is reduced to extend frame duration for better low light performance. When motion is minimal, the frame rate is increased to ensure smooth video playback. This dynamic adaptation allows the system to optimize between video smoothness and frame duration in real-time.
Data Source
AI summary
This disclosure provides systems, methods, and devices for image processing that support improved image quality. In a first aspect, a method of image processing includes determining a scene condition for an image sensor of an image capture device; receiving motion data regarding movement of the image capture device; configuring the image sensor of the image capture device with a first image sensor configuration determined based on the motion data and the scene condition; receiving image data from the image sensor captured with the first image sensor configuration; and determining a video sequence by processing the image data based on the motion data and the scene condition. Other aspects and features are also claimed and described.