Linear Histogram Overlay for Image Brightness Interpretation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face difficulty in understanding and interpreting image histograms due to their complex two-dimensional representation, which can obscure the image and hinder quick perception of brightness levels, leading to potential confusion or errors in image evaluation.
Innovation Solution
A linear representation of the image histogram is created using representative colors, where each position corresponds to a brightness level, allowing for a more intuitive and space-efficient display that overlays or positions adjacent to the image without obscuring it, using a grayscale color palette and mathematical calculations to determine color values based on histogram values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a two-dimensional image histogram is used to represent brightness levels, then comprehensive brightness information is provided, but the representation becomes complex and obscures the image
Solution Approach 1:
The patent transforms the traditional two-dimensional histogram representation into a one-dimensional linear representation that overlays the image. This dimensionality change simplifies the visual complexity while preserving brightness distribution information through color-coded pixels, where each pixel's color indicates the brightness level of the corresponding image region.
Solution Approach 2:
The patent merges the histogram data with the image display by overlaying colored pixels directly on the image. This combination allows users to perceive both the image content and brightness distribution simultaneously, eliminating the need for separate histogram visualization and reducing overall complexity.
2Loss of information
If a two-dimensional image histogram is displayed separately from the image, then complete brightness analysis is possible, but the image and histogram occupy excessive display space
Solution Approach 1:
The patent nests the histogram representation within the image display area by overlaying colored pixels directly on top of the image. This nesting approach allows the brightness distribution data to be embedded within the existing image space, eliminating the need for additional display area while preserving all brightness information.
Solution Approach 2:
By transitioning from a separate two-dimensional histogram to an overlaid one-dimensional representation, the patent compresses the brightness data into the image's existing spatial dimensions, maximizing information density within the available display area.
3Measurement precision
If traditional histogram representation is used, then detailed brightness values are shown, but users have difficulty quickly perceiving and understanding the information
Solution Approach 1:
The patent uses color-coded pixels to represent different brightness levels, where each pixel's color directly corresponds to the brightness value of the associated image region. This visual encoding allows users to quickly perceive brightness distribution through intuitive color patterns, dramatically improving perception speed while maintaining precise brightness information.
Solution Approach 2:
The patent changes the representation parameter from numerical or bar-based histogram values to color-coded visual indicators. This parameter transformation enables users to instantly grasp brightness levels through human color perception, which is far faster than interpreting traditional histogram data, while preserving the same level of measurement precision.
Data Source
AI summary
A method comprising determining an image histogram associated with an image, determining a linear image histogram based, at least in part, on the image histogram, and causing display of a linear representation of the image histogram and, at least part of, the image is disclosed.