Gradation Correction Evaluation Using Histogram Weighting
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Solution Overview
Problem
Existing image processing methods cannot optimize brightness and contrast effectively through gradation correction characteristics calculated by histogram equalization, making it difficult to determine if the correction will result in the best possible improvement.
Innovation Solution
A gradation correction characteristics evaluation device and method that creates a histogram based on pixel values, evaluates gradation correction characteristics, and applies weighting coefficients to normalize the histogram, allowing for the evaluation of multiple sets of gradation correction characteristics and their application to specific image areas, including face detection for enhanced weighting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If histogram equalization is used to calculate gradation correction characteristics, then brightness and contrast can be improved, but it cannot always optimize the image quality and the correction effectiveness cannot be judged in advance
Solution Approach 1:
The patent applies preliminary action by evaluating gradation correction characteristics before actually applying the correction to the image. The system calculates multiple candidate correction characteristics, evaluates them using the histogram-based evaluation index, and selects the optimal one in advance, allowing the correction effectiveness to be judged before execution.
Solution Approach 2:
The patent implements feedback by using the histogram evaluation index to assess the quality of gradation correction characteristics. The system calculates the histogram of the input image, evaluates candidate correction characteristics against this histogram, and uses the evaluation results to select the best correction, creating a closed-loop quality assessment mechanism.
2Measurement precision
If multiple sets of gradation correction characteristics are evaluated, then optimal correction can be selected, but the processing complexity increases
Solution Approach 1:
The patent applies self-service by using the image's own histogram characteristics to evaluate and select the optimal gradation correction. The system uses the input image's histogram as the basis for evaluating correction characteristics, allowing the image itself to provide the criteria for its own optimal correction without requiring external reference images or complex manual adjustment mechanisms.
Solution Approach 2:
The patent applies parameter changes by evaluating multiple different gradation correction characteristics (different transformation functions) and selecting the optimal one based on the histogram evaluation index. This allows the system to adjust the correction parameters dynamically to match the specific characteristics of each input image.
Data Source
AI summary
A gradation correction characteristics evaluation device includes: a histogram creation unit that creates a histogram based upon pixel values indicated at pixels constituting an input image; and an evaluation unit that evaluates gradation correction characteristics, which is used to correct gradation of the image, based upon the histogram of the image having been created by the histogram creation unit and the gradation correction characteristics.