Image Sensor Motion Correction via Segmented Pixel Readout
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Solution Overview
Problem
Current digital cameras face challenges in low-light conditions due to camera motion during exposure, leading to poor image quality and noise amplification, with existing solutions being costly or inefficient, such as optical image stabilization, mechanical methods, and blind deconvolution algorithms.
Innovation Solution
The method involves defining multiple sets of image element acquisition devices on an image sensor, with signals from these devices being read out multiple times to process and correct for camera motion through deblurring, spatial alignment, and sharpening, using techniques like block-matching and integral projections to estimate and correct for motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If exposure time is increased to boost photons in low-light conditions, then image brightness is improved, but image sharpness deteriorates due to camera motion
Solution Approach 1:
The patent divides the image sensor into multiple sets of image pixels (e.g., first set, second set, third set) that are read out at different times during the exposure period. This segmentation allows the system to capture motion information from multiple temporal snapshots while maintaining the total exposure duration, thereby preserving both brightness and sharpness.
Solution Approach 2:
The patent performs preliminary readouts of selected image pixel sets before the final image is complete. These preliminary readouts capture motion information that is used to estimate and correct camera motion during the exposure, allowing motion compensation to be applied before the final image is finalized.
2Illumination intensity
If digital gain factor is applied to boost light intensity, then image brightness is improved, but noise levels increase
Solution Approach 1:
By segmenting the sensor into multiple pixel sets read at different times, the system captures sufficient signal information during the total exposure period without needing to amplify noise through digital gain. The motion estimation from segmented reads enables motion compensation that reduces the need for aggressive gain application.
3Measurement precision
If optical image stabilization with gyroscopic measurement and lateral actuators is used, then camera motion correction is improved, but device cost and complexity increase
Solution Approach 1:
The patent replaces mechanical gyroscopic measurement and lateral actuator systems with an electronic solution. By using multiple image pixel sets read at different times and applying block-matching algorithms to estimate motion, the system achieves camera motion correction without mechanical components, significantly reducing cost and complexity.
Solution Approach 2:
The patent creates multiple temporal copies of image data by reading different pixel sets at different times during the exposure. These copies are then processed using block-matching to estimate motion, providing a software-based alternative to hardware stabilization systems.
4Measurement precision
If mechanical methods with gyroscopic measurements are used to track camera motion, then motion measurement precision is improved, but device cost and complexity increase
Solution Approach 1:
The patent substitutes mechanical gyroscopic measurement systems with an electronic motion estimation approach. By reading multiple pixel sets at different times and applying block-matching algorithms to the captured data, the system achieves accurate motion measurement without mechanical gyroscopes, reducing both cost and complexity.
5Measurement precision
If strips of sensor pixels are dedicated to motion estimation, then camera motion tracking is improved, but spatial resolution of output image decreases
Solution Approach 1:
The patent segments the sensor into multiple pixel sets that are read at different times during the exposure. This temporal segmentation allows motion estimation using the same spatial pixels that contribute to the final image, avoiding the need to dedicate separate spatial regions for motion tracking and thereby preserving spatial resolution.
Solution Approach 2:
The patent moves motion estimation from the spatial dimension to the temporal dimension by reading different pixel sets at different times. This allows motion information to be extracted from temporal variations in the same spatial pixels, preventing loss of spatial resolution while maintaining motion tracking capability.
6Device complexity
If blind deconvolution algorithms are used to reduce camera motion blur, then image processing is simplified, but correction accuracy decreases due to lack of motion knowledge
Solution Approach 1:
The patent performs preliminary readouts of multiple pixel sets during the exposure to capture motion information. This preliminary action provides actual motion data that is used to guide the deconvolution process, improving correction accuracy compared to blind deconvolution while maintaining reasonable processing complexity.
Solution Approach 2:
The patent uses block-matching algorithms to estimate motion from the multiple pixel set readouts, providing feedback about actual camera motion during the exposure. This feedback information is then used to guide the image processing, improving correction accuracy over blind deconvolution methods that lack such feedback.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively reduces camera motion blur and noise in low-light conditions, improving image quality without the need for additional costly hardware or assumptions about motion during exposure.
Implementation Method 1
an image sensor is defined. Multiple sets of image pixels are defined on the image sensor. Signals from a first set of image pixels are read out multiple times. Signals from a second set of image pixels are read out multiple times.
Data Source
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AI summary
A system and method for determining and correcting for imaging device motion during an exposure is provided. According to various embodiments of the present invention, multiple sets of image pixels are defined on an image sensor, where each set of pixels is at least partially contained in the output image area of the image sensor. Signals from each set of image pixels are read out once or more during an exposure, motion estimates are computed using signal readouts from one or more sets of image pixels, and signal readouts from one or more sets of the image pixels are processed to form the final output image.