Image Processing Apparatus Gradation Conversion via Partial Image Analysis
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Solution Overview
Problem
Existing image gradation conversion methods face challenges in achieving accurate analysis and appropriate gradation when joining multiple partial images, leading to increased processing load and potential loss of detail in large image shooting methods.
Innovation Solution
An image processing apparatus that acquires and analyzes feature amounts from partial images, determines a gradation conversion processing characteristic based on the shooting region, and converts the gradation of the joined image using these characteristics, allowing for accurate and efficient gradation conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If gradation conversion is performed based on a density histogram of a joined image, then the gradation of the whole image can be appropriate, but the processing load increases and accurate analysis becomes more difficult
Solution Approach 1:
The patent divides the large image into multiple partial images and performs gradation conversion on each partial image separately using its own density histogram, rather than processing the entire joined image as one unit. This segmentation approach maintains gradation accuracy for each region while reducing the overall processing load and memory requirements.
Solution Approach 2:
The patent applies different gradation conversion characteristics to different partial images based on their local density histograms and shooting regions. Each partial image receives customized gradation processing tailored to its specific characteristics, ensuring local optimization without requiring full-image processing.
2Device complexity
If gradation conversion is performed on a large image based on one partial image, then processing is simpler, but the whole large image may not have an appropriate gradation
Solution Approach 1:
The patent combines the gradation conversion results from multiple partial images, each processed with its own density histogram analysis. By merging these locally-optimized conversions into the final joined image, the system achieves both processing efficiency and overall gradation appropriateness.
Solution Approach 2:
The patent performs density histogram analysis and gradation conversion preparation on each partial image before the final joining process. This preliminary processing ensures that each partial image is optimally converted in advance, so that when joined, the entire large image achieves appropriate gradation without requiring complex post-processing.
3Productivity
If multiple partial images are processed individually for gradation conversion, then processing time is reduced, but the consistency of gradation across the whole image may be compromised
Solution Approach 1:
The patent applies a universal density histogram-based gradation conversion method to all partial images. This universal approach ensures that the same processing logic and criteria are used across all partial images, maintaining consistency and uniformity in the final joined image while enabling parallel processing for efficiency.
Data Source
AI summary
An image processing apparatus includes an image acquisition unit configured to acquire a plurality of partial images obtained by shooting each of a plurality of shooting ranges which a shooting region of an object are divided into, a feature amount acquisition unit configured to acquire a feature amount of at least one of the partial images, a characteristic acquisition unit configured to acquire a gradation conversion processing characteristic based on the feature amount and the shooting region, and a conversion unit configured to convert, based on the processing characteristic, a gradation of an image of the shooting region of the object obtained by joining the partial images.