Tone Mapping for Image Edge Accuracy and Detail Preservation
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Solution Overview
Problem
Tone mapping in image processing often results in reduced image quality at low and high gray regions, and inaccurately displays image edges due to differences in dynamic ranges between original image data and display devices.
Innovation Solution
An image processing method that performs tone mapping using different conversion functions based on the gray level of image data, applying a first tone mapping operation for non-edge regions and a second tone mapping operation for edge regions within specific gray ranges, and includes a bypass operation for images with a high number of edge pixels, to maintain detail and prevent distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a single tone mapping operation is applied to the entire image, then the processing is simple and fast, but the image quality at low and high gray regions deteriorates and edge accuracy is reduced
Solution Approach 1:
The image is divided into multiple regions based on gray level characteristics: low gray region (0-63), middle gray region (64-191), and high gray region (192-255). Different tone mapping operations are applied to each region, allowing optimized processing for each specific gray level range while maintaining overall image quality and edge accuracy.
Solution Approach 2:
Different tone mapping conversion functions are applied to different regions of the image based on their gray level characteristics. The first tone mapping operation uses a conversion function optimized for low gray regions, while the second tone mapping operation uses a different conversion function for high gray regions, ensuring each region receives appropriate processing quality.
2Adaptability or versatility
If tone mapping is applied to convert dynamic range, then the image adapts to display device capabilities, but detail loss occurs in low and high gray regions
Solution Approach 1:
The tone mapping process segments the image into different gray level regions and applies region-specific conversion functions. This segmentation prevents uniform compression that causes detail loss, allowing each region to be mapped with appropriate precision to preserve image details while adapting to display device dynamic range capabilities.
Solution Approach 2:
Different conversion functions with different parameters are applied to different gray level regions. The first conversion function is optimized for low gray regions while the second conversion function is optimized for high gray regions, allowing the system to adapt to display device dynamic range while preserving image details through parameter optimization for each region.
3Manufacturing precision
If a first tone mapping operation is used for all regions, then processing is consistent and simple, but edge portions in high gray regions are not accurately displayed
Solution Approach 1:
The image processing is segmented into different operations based on region characteristics. Edge detection is performed to identify edge portions, and then the first tone mapping operation is applied to non-edge regions while the second tone mapping operation is applied to edge regions in high gray levels, ensuring edge accuracy while maintaining processing organization.
Solution Approach 2:
The tone mapping process applies different conversion functions to different regions based on their characteristics. Edge regions in high gray levels receive a specialized conversion function that preserves edge accuracy, while non-edge regions receive a different conversion function optimized for their characteristics, ensuring local quality optimization throughout the image.
Data Source
AI summary
In an image processing method that converts image data into output data by performing tone mapping, an edge of an image represented by the image data is determined, a first tone mapping operation is performed on first image data included in the image data, where the first image data represent a first portion of the image not including the edge, whether a gray level of second image data is within a predetermined gray range is determined, where the second image data represent a second portion of the image including the edge, a second tone mapping operation is performed on the second image data when the gray level of the second image data is within the gray range, and the first tone mapping operation is performed on the second image data when the gray level of the second image data is not within the gray range.