Edge-Based Image Stabilization Reducing Pixel Processing
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Solution Overview
Problem
Conventional electronic image stabilization techniques require capturing and processing additional pixels beyond the field of interest, leading to increased bandwidth and power consumption, which results in thermal issues and reduced battery life.
Innovation Solution
The implementation of edge-based image stabilization techniques, such as pinned-edge and soft pinned-edge stabilization, where the image stabilization system applies a warping function to shift pixels non-uniformly, allowing the captured frame size to match the stabilized output, thereby reducing the number of discarded pixels and minimizing bandwidth and power requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional electronic image stabilization captures a buffer frame significantly larger than the field of interest, then image stabilization is achieved, but the number of pixels to be processed increases, leading to increased bandwidth requirements and power consumption
Solution Approach 1:
The patent extracts only the necessary portion of the buffer frame for stabilization processing. Instead of processing the entire oversized buffer frame, the system identifies and processes only the region containing the field of interest, thereby reducing the number of pixels processed while maintaining stabilization effectiveness
Solution Approach 2:
The patent applies different processing quality levels to different regions of the buffer frame. The field of interest region receives full stabilization processing, while the surrounding buffer regions are either processed with reduced quality or discarded, optimizing the balance between stabilization performance and processing resource consumption
2Reliability
If conventional electronic image stabilization captures a buffer frame significantly larger than the field of interest, then image stabilization is achieved, but the bandwidth requirements of image sensors and DSPs increase
Solution Approach 1:
The system extracts and processes only the essential region of the buffer frame that contains the field of interest. This extraction approach reduces the data volume that needs to be transmitted through the bandwidth-constrained channels between the image sensor, DSP, and other processing components
Solution Approach 2:
The buffer frame is segmented into the field of interest region and the surrounding buffer regions. Only the field of interest segment is processed for stabilization, reducing the total pixel count that requires bandwidth-consuming data transfer and processing
3Reliability
If conventional electronic image stabilization captures additional pixels beyond the field of interest, then image stabilization is achieved, but thermal problems with camera electronics worsen
Solution Approach 1:
The patent extracts only the necessary field of interest region from the buffer frame for processing. This reduces the computational workload and associated heat generation in the camera electronics, while still achieving effective image stabilization for the captured content
4Reliability
If conventional electronic image stabilization captures additional pixels beyond the field of interest, then image stabilization is achieved, but battery life is reduced
Solution Approach 1:
The system extracts and processes only the essential field of interest region, significantly reducing the number of pixels that require processing. This reduction in processing workload directly decreases power consumption, thereby extending battery life while maintaining effective image stabilization
Solution Approach 2:
The patent applies full stabilization processing only to the field of interest region rather than the entire buffer frame. This localized processing approach reduces overall computational requirements and power consumption, preserving battery life for extended camera operation
Data Source
AI summary
An image stabilization system applies a “pinned-edge” or “soft pinned edge” image stabilization technique to digital video to compensate for unwanted camera motion in a captured video. In these stabilization techniques, a warping function is applied to an image frame to achieve a non-uniform shifting of depicted points in the image frame such that a reference point is stabilized with respect to a reference frame. In pinned-edge image stabilization, the final stabilized output video has the same dimensions as the pre-stabilized input video captured by the image sensor. In soft pinned-edge image stabilization, the pre-stabilized input video has slightly larger dimensions than the stabilized output video but these larger dimensions are still reduced compared to traditional electronic image stabilization.