Image Processing Apparatus for Composite Image Visual Coherence
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Solution Overview
Problem
Existing image processing methods often result in a composite image with a sense of discomfort when attaching an outdoor image to an indoor scene, as they fail to effectively reflect the features of the scene into the attachment image.
Innovation Solution
An image processing apparatus that includes a composite image generation unit, a feature quantity acquisition unit, and a reflection unit, which acquires feature quantities of the scene image and adjusts the attachment image using these features to reduce the sense of discomfort by reflecting scene image characteristics into the attachment image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing image processing methods are used to attach images, then the attachment operation is simple and fast, but the composite image has a sense of discomfort due to lack of feature reflection
Solution Approach 1:
The system performs preliminary analysis of the scene image to extract feature quantities (color distribution, luminance characteristics, texture patterns) before the attachment operation. This pre-processing enables the attachment image to be adjusted in advance to match the scene's characteristics, resolving the contradiction by preparing the feature reflection data beforehand rather than during the attachment operation itself.
Solution Approach 2:
The system changes multiple parameters of the attachment image simultaneously based on scene features: color balance adjustment to match scene color distribution, luminance scaling to align with scene brightness characteristics, and contrast modification to reflect scene texture patterns. This multi-parameter adjustment approach maintains operational simplicity while significantly improving visual coherence.
2Manufacturing precision
If feature reflection processing is added to attach images, then the visual coherence of composite image is improved, but the processing complexity and time increase
Solution Approach 1:
The feature reflection process is segmented into three independent modules: color distribution analysis, luminance characteristic extraction, and texture pattern recognition. Each module processes specific features separately and applies corresponding adjustments to the attachment image. This segmentation reduces overall system complexity by breaking down the complex feature reflection task into manageable, specialized components.
Solution Approach 2:
The system introduces a feature quantity acquisition unit as an intermediary between the scene image and the attachment image processing. This intermediary extracts and quantifies scene characteristics (color histograms, luminance profiles, texture descriptors) and uses them as reference data to guide the attachment image adjustments, simplifying the overall process by mediating through standardized feature representations.
3Measurement precision
If comprehensive feature analysis is performed on the scene image, then the accuracy of feature reflection is improved, but the processing time increases
Solution Approach 1:
The system implements a multi-level feature analysis approach: it performs comprehensive feature extraction (color, luminance, texture) only when high visual coherence is required, while providing a faster attachment mode for less demanding scenarios. This partial action strategy allows users to balance accuracy and processing time based on specific needs, achieving high measurement precision only when necessary.
Solution Approach 2:
The system pre-calculates and stores feature quantities (color distributions, luminance characteristics, texture patterns) from the scene image before the actual attachment operation. This preliminary analysis creates a reference profile that can be quickly applied during attachment, reducing real-time processing time while maintaining high accuracy of feature reflection.
Data Source
AI summary
Provided is an image processing apparatus including a composite image generation unit that composes a first image that is an attachment target image and a second image to be attached to the first image to generate a composite image in which the second image is included in the first image, a feature quantity acquisition unit that acquires a feature quantity of the first image, and a reflection unit that reflects a feature of the first image into the second image using the feature quantity of the first image acquired by the feature quantity acquisition unit.