Distance Image Formation Error Correction Without Pre-stored Data
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Solution Overview
Problem
Existing image processing technologies require pre-stored data in a recording medium to correct distance information errors during correlation computation, limiting their ability to accurately form distance images.
Innovation Solution
An image processing apparatus with a distance estimation unit, reliability calculation unit, and image forming unit that estimates subject distance, calculates reliability, and corrects errors without pre-stored data, using correlation degree computations and defocus amount calculations to form accurate distance images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pre-stored correction data is held in a recording medium to correct distance information errors, then measurement precision of distance information is improved, but device complexity increases due to additional storage requirements
Solution Approach 1:
The system performs self-correction by using the captured images themselves to calculate defocus amounts and correct distance information errors, eliminating the need for external pre-stored correction data. The correction data is generated on-demand from the image data, allowing the system to serve its own correction needs without additional storage components.
Solution Approach 2:
The defocus amount calculation acts as an intermediary process that bridges the raw image data and the final distance measurement. By introducing this intermediate calculation step, the system can correct distance errors dynamically without requiring pre-stored correction tables, thus reducing device complexity while maintaining precision.
2Reliability
If pre-stored correction data is held in a recording medium, then reliability of distance information is improved, but loss of information increases due to storage dependencies
Solution Approach 1:
The system generates correction information on-demand from the captured images themselves, eliminating dependency on pre-stored data. This self-service approach ensures that correction data is always derived from the actual image content, improving reliability while avoiding the information loss associated with storing and retrieving pre-computed correction tables.
Solution Approach 2:
The system performs preliminary defocus amount calculation from the captured images before final distance measurement, preparing correction data in advance for the specific imaging conditions. This preliminary action ensures reliable correction without needing to store generic correction data, as the correction is tailored to each specific image capture scenario.
3Productivity
If correlation degree computation is performed without error correction, then productivity is improved by simplifying processing, but measurement precision deteriorates due to computation errors
Solution Approach 1:
The system automatically calculates defocus amounts from the captured images and uses these to correct correlation computation errors on-the-fly. This self-service correction mechanism adds minimal processing overhead while significantly improving measurement precision, maintaining productivity without requiring complex pre-stored correction data.
Solution Approach 2:
The system implements a feedback loop where defocus amounts calculated from images are used to correct distance measurement errors. This feedback mechanism continuously improves measurement precision by compensating for correlation computation errors, achieving high accuracy without sacrificing processing speed through elaborate pre-computed correction schemes.
Data Source
AI summary
An image processing apparatus capable of correcting an error during computation of a correlation degree without storing data for correcting distance information in advance in a recording medium, to highly accurately form a distance image. The image processing apparatus has a distance estimation unit that estimates a subject distance in each area, from a correlation degree of a plurality of images, a distance reliability calculation unit that calculates the reliability of the subject distance estimated by the distance estimation unit, and a distance image forming unit that corrects the subject distance estimated by the distance estimation unit based on the reliability calculated by the distance reliability calculation unit and to form a distance image based on the corrected subject distance.