Image Composition Brightness Correction via Local Region Analysis

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Solution Overview

Problem

Existing image processing techniques for depth composition do not ensure proper brightness across all regions of a composite image, particularly when capturing subjects at different distances, leading to potential under or overexposure issues.

Innovation Solution

An image processing apparatus that captures multiple images at varying focus positions, calculates contrast-related values, generates a composition map, divides regions based on subjects, and adjusts the gradation using gain correction to ensure proper brightness across all regions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If depth composition is performed by combining multiple images with different focus positions, then the entire imaging region becomes focused, but the brightness of composed regions may become unsuitable for the subject

Engineering Contradiction:
Improvefocus precisionVSAvoidbrightness
Core Design Contradiction:
Measurement precisionVSIllumination intensity

Solution Approach 1:

The patent applies local quality by dividing the image into multiple regions and applying different brightness correction methods to each region. The brightness correction unit selectively corrects brightness for specific regions (such as sky regions or regions with large brightness differences) rather than uniformly correcting the entire image, thus maintaining subject-appropriate brightness while preserving depth composition focus quality.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The patent changes the brightness parameter selectively for specific regions by calculating brightness correction amounts based on region characteristics. The brightness correction unit adjusts the brightness parameter (illumination intensity) for regions where it is inappropriate, while leaving other regions unchanged, thereby resolving the contradiction between focus precision and brightness appropriateness.

Inventive Principle:
Principle #35Parameter changes

2Reliability

If multiple images with different focus positions are combined, then comprehensive focus coverage is achieved, but inconsistent brightness across regions occurs

Engineering Contradiction:
Improvefocus coverageVSAvoidbrightness consistency
Core Design Contradiction:
ReliabilityVSStability of the object's composition

Solution Approach 1:

The patent addresses brightness consistency by applying localized brightness correction to specific regions rather than uniformly processing the entire image. The brightness correction unit identifies regions with inappropriate brightness (such as sky regions or regions with large brightness differences between composed images) and corrects only those areas, maintaining overall composition stability while ensuring local brightness appropriateness.

Inventive Principle:
Principle #3Local quality

Solution Approach 2:

The patent employs feedback by calculating brightness correction amounts based on the actual brightness characteristics of each region. The brightness correction unit analyzes the brightness distribution in composed regions and applies corrective adjustments based on this feedback, thereby maintaining brightness consistency across the composite image while preserving the comprehensive focus coverage achieved through depth composition.

Inventive Principle:
Principle #23Feedback

Data Source

PatentUS12100122B2Image processing apparatus for combining a plurality of images, imaging apparatus, imaging method, and recording medium
Publication Date: 2024.09.24 CANON KK
  • US12100122B2 patent drawing
  • US12100122B2 patent drawing
  • US12100122B2 patent drawing

AI summary

An apparatus includes at least one memory configured to store instructions, and at least one processor coupled to the at least one memory and configured to execute the instructions to perform image composition of a plurality of images with different focus positions, calculate contrast-related values based on the plurality of images, generate a composition map based on the contrast-related values, divide a region based on subjects with respect to the plurality of images, and correct a gradation for the each region that has been divided.