Contrast Enhancement Using Local Intensity Gradient Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for automatic contrast enhancement of digital images, such as histogram equalization, often result in unrealistic representations and are inefficient for video streams, as they require manual intervention and are time-consuming.
Innovation Solution
A method that calculates contrast values based on intensity gradients between pixels, selects pixels meeting specific criteria, and applies tone mapping functions to expand or compress intensity values within selected ranges, using edge filters like Roberts, Sobel, or Laplacian filters, to produce a contrast-enhanced output image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If histogram equalization is used for automatic contrast enhancement, then contrast improvement is achieved, but the image representation becomes unrealistic
Solution Approach 1:
The patent applies different processing treatments to different regions of the image based on local characteristics. By calculating contrast values for individual pixels and selecting pixels that meet specific criteria, the method selectively enhances certain intensity ranges while preserving the realism of other regions, thereby resolving the contradiction between contrast enhancement and image realism.
Solution Approach 2:
The patent dynamically adjusts the tone mapping function parameters based on the selected pixels and their intensity distribution. By changing the enhancement parameters selectively for different intensity ranges rather than applying uniform histogram equalization, the method achieves both improved contrast and maintained image realism.
2Manufacturing precision
If manual contrast enhancement is applied to still images, then visually appealing results are achieved, but the process is time consuming
Solution Approach 1:
The patent enables the system to automatically determine which pixels to alter and how to apply tone mapping by calculating contrast values and selecting pixels based on predefined criteria. This self-service approach eliminates the need for manual intervention while maintaining high-quality contrast enhancement results, thereby resolving the time consumption issue.
Solution Approach 2:
The patent replaces the manual mechanical process of adjusting tone mapping functions with an automated computational system that calculates contrast values and applies enhancement algorithms. This substitution of manual operations with automated processing significantly reduces processing time while preserving enhancement quality.
3Extent of automation
If conventional contrast enhancement methods are used for video streams, then automatic processing is attempted, but the methods are inefficient and not useful for sequential frames
Solution Approach 1:
The patent performs preliminary calculations of contrast values for each pixel before applying the tone mapping function. By pre-identifying which pixels meet the selection criteria and organizing them into intensity distributions, the method streamlines the subsequent enhancement process, making it efficient enough for real-time video stream processing while maintaining full automation.
4Manufacturing precision
If pixel intensity values are expanded to enhance contrast, then detail in similar intensity areas is improved, but the overall image dynamic range is reduced
Solution Approach 1:
The patent applies selective expansion only to specific intensity ranges that contain pixels meeting the contrast criteria, rather than uniformly expanding all intensity values. This localized approach enhances detail in areas needing improvement while preserving the overall dynamic range of the image, resolving the contradiction between detail visibility and intensity range coverage.
Data Source
AI summary
A method and apparatus for enhancing an input image to produce a contrast enhanced output image is disclosed. The method involves producing a contrast value for each pixel in the input image, the contrast value being proportional to an intensity gradient between each respective pixel and at least one pixel adjacent the respective pixel. The method also involves selecting pixels in the input image having respective contrast values that meet a first criterion, thereby forming a selected plurality of pixels and producing a frequency distribution of intensity values of the selected plurality of pixels. The method further involves selecting at least one range of intensity values in the frequency distribution that meet a second criterion, thereby producing a selected range of intensity values for enhancement. The method also involves producing the contrast enhanced output image by at least one of (i) expanding pixel intensity values in the input image that fall within the selected range of intensity values; and (ii) compressing pixel intensity values in the input image that fall outside the selected range of intensity values.