Motion-Compensated Image Processing for Low-Light Noise Reduction
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Solution Overview
Problem
The use of smaller and lower quality image sensor chips in computer devices results in degraded low-light performance, leading to noisy and low-quality images, which existing technologies have not adequately addressed.
Innovation Solution
A multistage image processing system that applies motion compensation techniques using multi-window motion analyzers and infinite impulse response filters to detect and correct motion, enhancing image quality by correlating frames and adjusting settings based on detected motion and confidence information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If smaller and lower quality image sensor chips are used to reduce cost and size, then device cost and size are reduced, but image quality and low light performance deteriorate
Solution Approach 1:
The patent uses temporal copying by capturing multiple frames over time and combining them to create a higher quality output image. The motion compensation technique copies information from multiple temporal instances (frames) and synthesizes a denoised image, effectively creating a virtual high-quality sensor through software processing of multiple lower-quality captures
Solution Approach 2:
The patent merges multiple frames captured at different time points by aligning them using motion compensation and combining their pixel values. This merging process integrates information from multiple temporal sources to produce a single output frame with reduced noise and improved quality, overcoming the limitations of individual frame quality
2Volume of moving object
If smaller image sensor chips are used, then device size is reduced, but noise in captured images increases
Solution Approach 1:
The system captures multiple temporal copies (frames) of the same scene and combines them to reduce noise. By copying the scene multiple times and processing these copies together, the system eliminates random noise while preserving signal information, effectively reducing the harmful noise effect
Solution Approach 2:
The patent converts the harmful effect of noise into a benefit by using the temporal redundancy of multiple noisy frames. The noise, while harmful in individual frames, provides additional information when multiple frames are combined through motion-compensated averaging, ultimately reducing noise in the final output
3Manufacturing precision
If motion compensation processing is applied to reduce noise, then image quality improves, but processing complexity increases
Solution Approach 1:
The patent segments the image processing task into distinct stages: motion detection, motion compensation, and frame combination. By dividing the complex processing into modular segments, the system manages computational complexity more effectively while achieving high-quality noise reduction through systematic processing of motion information
Data Source
AI summary
An image processing system receives a sequence of frames including a current input frame and a next input frame (the next input frame is captured subsequent in time with respect to capturing of the current input frame). The image processing system stores a previously outputted output frame. The previously outputted output frame is derived from previously processed input frames in the sequence. The image processing modifies the current input frame based on detected first motion and second motion. The first motion is detected based on an analysis of the current input frame with respect to the next input frame. The second motion is detected based on an analysis of the current input frame with respect to the previously outputted output frame. According to one configuration, the image processing system implements multi-sized analyzer windows to more precisely detect the first motion and second motion.