Image Processing Device Region-Based Saturation Adjustment
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Solution Overview
Problem
Conventional image processing methods fail to effectively differentiate and enhance the main object in an image by accurately adjusting saturation and color characteristics, leading to a lack of distinction and clarity.
Innovation Solution
An image processing device and method that sets a main object region and a non-object region, calculates image characteristic amounts, compares them to determine a saturation emphasis coefficient, and applies image processing methods to adjust saturation and color, enhancing the main object's visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional saturation correction methods are used, then overall image saturation is improved, but the main object cannot be effectively differentiated from the background
Solution Approach 1:
The image is divided into multiple regions including a main object region and a background region. Saturation correction is applied differently to each region based on its characteristics. The main object region undergoes one level of saturation adjustment while the background region undergoes a different level, enabling both overall saturation improvement and object differentiation.
Solution Approach 2:
Different saturation correction parameters are applied to different spatial locations in the image. The main object region receives a first saturation correction parameter while the background region receives a second saturation correction parameter, creating local quality variations that enhance object visibility and distinction.
2Ease of operation
If uniform saturation correction is applied to the entire image, then processing simplicity is maintained, but the main object becomes indistinguishable from the background
Solution Approach 1:
The image processing is segmented into region identification and differential correction stages. The system automatically identifies the main object region and applies different saturation parameters to it compared to the background, maintaining operational simplicity while achieving precise object enhancement.
Solution Approach 2:
The system automatically performs region segmentation and determines appropriate saturation parameters for each region without requiring manual intervention. The main object region is automatically identified and processed with appropriate parameters, making the complex differential correction process as simple as uniform correction from the user perspective.
Data Source
AI summary
An image processing device that corrects an obtained image includes: an image acquisition unit that obtains the image; a region setting unit that sets a first region including a main object and a second region not including the main object on the image; an image characteristic amount calculation unit that calculates a first image characteristic amount respectively in the first region and the second region; a comparison unit that compares the first image characteristic amounts of the first region and the second region; an image processing method setting unit that sets an image processing method to be applied to the image, from a plurality of image processing methods, on the basis of a comparison result obtained by the comparison unit; and an image characteristic adjustment unit that adjusts a second image characteristic amount of the obtained image using the method set by the image processing method setting unit.