Color Correction Method for Image Sensor Fringe Elimination

Solution Overview

Problem

High-resolution images often suffer from color fringe issues due to chromatic aberration, requiring manual user intervention for correction, which is inefficient and suboptimal.

Innovation Solution

A color correction method that automatically detects and corrects color fringes by analyzing color distribution, identifying specific objects, and calibrating color deviation areas using a machine learning or similar algorithm to generate a calibrated image without color deviation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If manual operation is used to eliminate color fringe, then color fringe can be removed, but user time and operational complexity increase

Engineering Contradiction:

Improvecolor fringeVSAvoiduser time

Core Design Contradiction:

Object-affected harmful factorsVSLoss of time

Solution Approach 1:

The system performs automatic color fringe detection and correction without requiring user intervention. The processor autonomously analyzes the detection image, identifies color deviation areas, estimates correction color values, and generates calibrated images, enabling the image apparatus to correct its own defects

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical operation with an automated image processing system. The processor uses algorithmic analysis to detect color fringes and apply corrections, substituting human manual operations with automated computational processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Object-affected harmful factors

If manual operation is used to eliminate color fringe, then color fringe can be removed, but operational complexity increases

Engineering Contradiction:

Improvecolor fringeVSAvoidoperational complexity

Core Design Contradiction:

Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

The system performs automatic color fringe detection and correction without requiring user intervention. The processor autonomously analyzes the detection image, identifies color deviation areas, estimates correction color values, and generates calibrated images, enabling the image apparatus to correct its own defects

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical operation with an automated image processing system. The processor uses algorithmic analysis to detect color fringes and apply corrections, substituting human manual operations with automated computational processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Loss of time

If automatic color correction is implemented, then user time is saved, but color accuracy may deteriorate

Engineering Contradiction:

Improveuser timeVSAvoidcolor accuracy

Core Design Contradiction:

Loss of timeVSMeasurement precision

Solution Approach 1:

The system analyzes the detection image to identify color deviation areas and estimates correction color values based on the surrounding pixel values. This feedback mechanism ensures that corrections are tailored to the specific characteristics of each color fringe, maintaining color accuracy while automating the process

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent applies different correction strategies based on the local characteristics of color deviation areas. By analyzing color distribution within specific regions and estimating correction values based on surrounding pixels, the system adapts corrections to local image characteristics, preserving overall color accuracy

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11863916B2Color correction method and image correction apparatus

Publication Date: 2024.01.02 ALTEK SEMICON

AI summary

A color correction method is applied to an image correction apparatus having an image sensor, and includes searching a color deviation area within a detection image, analyzing the detection image to estimate a correction color value of the color deviation area, and calibrating the color deviation area by the correction color value to generate a calibrated detection image without color deviation.