Weighted Summing of Component Chiral Images for Contrast Enhancement

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Solution Overview

Problem

Existing contrast enhancement techniques in image processing often fail to provide optimal results across all scenarios, enhancing noise and requiring complex parameter tuning, and lack a single solution that works universally.

Innovation Solution

A method involving the capture of component chiral images using orthogonal polarized filters, pre-enhancement, weighting, and summing to generate a contrast-enhanced image, which optimizes contrast without increasing noise through iterative processing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Illumination intensity

If standard contrast enhancement algorithms are applied, then contrast is improved, but noise is also enhanced

Engineering Contradiction:

ImprovecontrastVSAvoidnoise

Core Design Contradiction:

Illumination intensityVSObject-generated harmful factors

Solution Approach 1:

The image is divided into multiple component chiral images based on polarization directions. Each component image is processed separately through weighting and summing, allowing contrast enhancement while maintaining noise control through the decomposition approach

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The final contrast-enhanced image is constructed as a composite of multiple weighted component chiral images. By combining images from different polarization directions with optimized weights, the method achieves superior contrast while the composite structure inherently suppresses noise amplification

Inventive Principle:

Principle #40Composite materials

2Illumination intensity

If complex contrast enhancement algorithms are used, then contrast improvement is achieved, but parameter tuning complexity increases

Engineering Contradiction:

ImprovecontrastVSAvoidparameter tuning complexity

Core Design Contradiction:

Illumination intensityVSDevice complexity

Solution Approach 1:

The system performs self-adjustment through automated weight optimization. The weight factors for each component chiral image are determined through optimization algorithms that automatically find the optimal combination, eliminating the need for manual parameter tuning by operators

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The method transforms the complex problem of contrast enhancement into a parameter optimization problem. By changing the weights of component images as the primary variable, the system achieves contrast enhancement through a single key parameter (weight optimization) rather than multiple sensitive parameters

Inventive Principle:

Principle #35Parameter changes

3Illumination intensity

If single image processing is performed, then processing speed is maintained, but contrast enhancement effectiveness is limited

Engineering Contradiction:

Improvecontrast enhancement effectivenessVSAvoidprocessing speed

Core Design Contradiction:

Illumination intensityVSProductivity

Solution Approach 1:

The image processing is segmented into component chiral images that can be processed in parallel. This decomposition allows the system to leverage parallel computing capabilities, maintaining high processing speed while achieving superior contrast enhancement through multiple image components

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Multiple component chiral images are merged through weighted summing to produce the final contrast-enhanced image. This combining operation integrates information from different polarization directions, achieving enhanced contrast effectiveness while the parallel processing of components maintains processing speed

Inventive Principle:

Principle #5Merging (Combining)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach provides improved contrast enhancement in real-time, enhancing both visible and infrared imagery, with reduced noise and minimal processing complexity, leveraging dual polarization imaging systems to create superior image detail.

Implementation Method 1

a first component chiral image being captured by a first filter that is polarized in a first direction; (b) receiving from the at least one imaging system a second component chiral image, the second component chiral image being captured by a second filter that is polarized in a second direction, the second direction being substantially orthogonal to the first direction

Methodology Applied

Scientific EffectPolarization: Polarisation

Data Source

PatentUS11080828B1Weighted summing of component chiral images for improved contrast enhancement

Publication Date: 2021.08.03 THE UNITED STATES OF AMERICA AS REPRESENTED BY THE SECRETARY OF THE NAVY

AI summary

Method and system for improved contrast enhancement. The method includes receiving, from at least one imaging system, first and second component chiral images, the first component chiral image being captured by a first filter that is polarized in a first direction, the second component chiral image being captured by a second filter that is polarized in a second direction, the second direction being substantially orthogonal to the first direction. The method also includes pre-enhancing, by a processor, one or both of said first component chiral image and said second component chiral image. Then the processor weights and sums at least a portion of the first and second component chiral images. Weighting and summing may be repeated until an optimal weight is reached. A contrast enhanced image may be generated after the optimal weight is reached.