Image Sensor Frame-to-Frame Lag Correction Using Truncated Row Data
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Solution Overview
Problem
High frame rates in image sensor devices result in unacceptably high lag due to the relaxation of high K dielectric materials, leading to unacceptable lag levels, especially in the last rows of the frame, which affects image quality and performance.
Innovation Solution
A method involving reading data from a current frame and correcting it using truncated data from the previous frame, applying dithering and scaling, and storing the corrected data in memory to mitigate lag, while optimizing memory usage and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high frame rates are used in image sensor devices, then productivity is improved, but lag increases due to relaxation of high K dielectric materials
Solution Approach 1:
The patent applies preliminary action by reading and storing truncated row data from the previous frame (N-1) before processing the current frame (N). This pre-prepared data is then used to calculate lag correction values, allowing the system to compensate for dielectric relaxation effects that occur during high-speed operation, thereby maintaining image quality at high frame rates
Solution Approach 2:
The patent changes parameters by truncating row data to specific bit depths (e.g., 2 least significant bits) and applying scaling factors based on reset duration and frame rate. These parameter transformations enable efficient memory storage while preserving sufficient information for lag correction, resolving the contradiction between high frame rate operation and image quality maintenance
2Reliability
If lag correction is applied using full row data from previous frames, then image quality is improved, but memory usage and power consumption increase
Solution Approach 1:
The patent extracts only the essential information needed for lag correction by truncating row data to retain only the most significant bits. This extraction process removes unnecessary data while preserving the critical information required for calculating lag correction values, thereby reducing memory bandwidth requirements and power consumption while maintaining image quality
Solution Approach 2:
The patent uses truncated row data as a simplified, low-cost approximation of full row data. By discarding less significant bits that contribute minimally to lag correction accuracy, the system achieves effective lag mitigation with reduced computational and memory resources, lowering overall power consumption
3Quantity of substance
If truncated row data is used for lag correction, then memory usage is reduced, but correction accuracy may be compromised
Solution Approach 1:
The patent applies parameter changes by systematically truncating row data to specific bit depths and applying compensating scaling factors. This transformation maintains the essential information needed for accurate lag correction while optimizing memory usage, achieving a balance between storage efficiency and correction precision
Solution Approach 2:
The patent applies different truncation levels to different portions of the data based on their importance for lag correction. By preserving the most significant bits that contain the critical lag information while discarding less significant bits, the system achieves accurate correction with reduced memory requirements
Data Source
AI summary
Implementations of a method of mitigating lag for an image sensor device may include reading a row of data from an Nth frame of image data from an image sensor device; correcting the row of data using truncated row data from an N−1th frame stored in a memory operatively coupled with the image sensor device to form a lag corrected row of data; outputting the lag corrected row of data; truncating the row of data to form truncated row data from the Nth frame; and storing the truncated row data from the Nth frame in the memory.