Image Detail Enhancement via Equilibrium Mapping and Sub-region Segmentation
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Solution Overview
Problem
Existing image processing methods struggle to perfectly highlight image details while achieving high-speed and effective calculation, particularly in balancing global and local histogram equalization algorithms.
Innovation Solution
The method involves determining an equilibrium mapping curve for a whole grayscale image in YUV mode, dividing it into sub-regions, and calculating mapping restriction parameters for each pixel. These parameters are used to adjust the grayscale values, optimizing detail enhancement and reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If local histogram equalization algorithm is used to enhance image details, then image detail enhancement is improved, but calculation amount increases hugely
Solution Approach 1:
The image is divided into multiple local regions, and each region is processed independently with its own equilibrium mapping curve. This segmentation allows detailed enhancement in each region while avoiding the need to process the entire image with full local histogram equalization complexity.
Solution Approach 2:
Different equilibrium mapping curves are applied to different local regions based on their specific characteristics. Each region receives customized processing parameters that optimize detail enhancement for that particular area, achieving local quality improvement without global computational overhead.
2Productivity
If global histogram equalization algorithm is used to reduce calculation amount, then calculation efficiency is improved, but image detail enhancement deteriorates
Solution Approach 1:
The image is divided into multiple local regions, and each region is processed independently with its own equilibrium mapping curve. This segmentation allows detailed enhancement in each region while avoiding the need to process the entire image with full local histogram equalization complexity.
Solution Approach 2:
Different equilibrium mapping curves are applied to different local regions based on their specific characteristics. Each region receives customized processing parameters that optimize detail enhancement for that particular area, achieving local quality improvement without global computational overhead.
3Manufacturing precision
If local histogram equalization is used to highlight image details, then image processing precision is improved, but calculation complexity increases
Solution Approach 1:
The image is divided into multiple local regions, and each region is processed independently with its own equilibrium mapping curve. This segmentation allows detailed enhancement in each region while avoiding the need to process the entire image with full local histogram equalization complexity.
Solution Approach 2:
Different equilibrium mapping curves are applied to different local regions based on their specific characteristics. Each region receives customized processing parameters that optimize detail enhancement for that particular area, achieving local quality improvement without global computational overhead.
Data Source
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AI summary
The present disclosure relates to an image processing method and device, which is configured to convert an obtained image to be processed into a grayscale chrominance YUV mode image; determine an equilibrium mapping curve of a whole grayscale image according to the grayscale image in the YUV mode image; divide the whole grayscale image into a plurality of sub-regions, and determine a mapping restriction parameter for each pixel in each of the sub-regions; adjust a grayscale value of each pixel in the grayscale image according to the determined equilibrium mapping curve of the whole grayscale image and the mapping restriction parameter of each pixel in each of the sub-regions; and convert the adjusted grayscale image into an image of original mode. When an image is being processed, an equilibrium mapping curve and a plurality of mapping restriction parameters can be used to present the details of the processed image well and greatly reduce the calculation amount, and the image of the display is effectively enhanced and the image details remain in case of high speed and low resource consumption.