PSF Estimation for Fine-Pattern Image Blur Correction

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Solution Overview

Problem

Existing image processing technologies struggle to accurately estimate the point spread function (PSF) for regions with fine patterns, leading to degraded image quality due to incorrect blur correction, particularly in sports images with swinging objects.

Innovation Solution

A method for improving PSF estimation by extracting a specific region, applying edge extraction and mask processing to exclude fine patterns, and using iterative methods to estimate the PSF accurately, followed by adding a blurring or deblurring effect based on the estimated PSF.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If PSF estimation is performed using fine lattice patterns (e.g., tennis racket strings) as reference, then the estimation process can be simplified, but the PSF estimation accuracy degrades because the fine patterns appear as shapes in the estimated characteristics rather than accurately representing blur

Engineering Contradiction:

ImprovePSF estimation process simplicityVSAvoidPSF estimation accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent applies local quality by selecting specific regions in the image that are suitable for PSF estimation. Instead of using the entire image or arbitrary regions, the system identifies regions with appropriate characteristics (avoiding fine lattice patterns) to perform PSF estimation. This ensures that the estimation is performed on locally suitable areas, improving accuracy while maintaining process simplicity.

Inventive Principle:

Principle #3Local quality

2Productivity

If incorrect PSF (estimated from fine lattice patterns) is used for correction processing, then the processing can be completed quickly, but image quality degrades due to inaccurate blur correction

Engineering Contradiction:

ImproveCorrection processing speedVSAvoidImage quality

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent applies preliminary action by performing region selection and suitability assessment before PSF estimation and correction processing. The system pre-identifies appropriate regions for PSF estimation, ensuring that the subsequent estimation and correction processes use accurate data. This preliminary step prevents the use of incorrect PSF while maintaining efficient processing.

Inventive Principle:

Principle #10Preliminary action

3Quantity of substance

If the entire image is used for PSF estimation, then more data is available for estimation, but the presence of fine lattice patterns and other distracting features degrades the estimation accuracy

Engineering Contradiction:

ImproveData volume for estimationVSAvoidPSF estimation accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent applies the taking out principle by extracting and selecting specific regions from the image that are suitable for PSF estimation. Instead of using the entire image, the system extracts regions that lack fine lattice patterns and other distracting features. This selective extraction maintains sufficient data volume for accurate estimation while eliminating harmful elements.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS12632939B2Apparatus, method, and non-transitory computer-readable storage medium

Publication Date: 2026.05.19 CANON KK

AI summary

An apparatus includes a determination unit configured to determine a specific region in an image, and a point spread function estimation unit configured to perform point spread function estimation for the specific region. The point spread function estimation unit is capable of performing at least one of edge extraction and mask processing on the image, and is configured to estimate a point spread function for the processed image.