Image Data Conversion Device Histogram Pattern Gamma Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image data conversion methods struggle to perform appropriate correction according to the characteristics of color images when converting them to black-and-white, often resulting in indistinct prints with blocked up colors or excessive image conversion issues in entirely bright or dark images.
Innovation Solution
An image data conversion device that represents color image data in grayscale, creates a histogram of brightness values, determines the image pattern, and applies gamma correction within specific ranges for each pattern to ensure accurate conversion to black-and-white, using techniques like histogram expansion and gamma correction to enhance contrast while preventing excessive image alteration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If gamma correction is applied to entire bright or dark images, then contrast is enhanced, but image quality deteriorates with blocked up shadows or blown out highlights
Solution Approach 1:
The patent applies different processing strategies to different regions of the histogram based on image brightness characteristics. For entirely bright images, the lower brightness region is fixed to preserve highlights while gamma correction is applied to the upper region. For entirely dark images, the upper brightness region is fixed to preserve shadows while gamma correction is applied to the lower region. This local differentiation resolves the contradiction by enhancing contrast only where appropriate without damaging image quality.
2Manufacturing precision
If histogram expansion is performed on entirely bright or dark images, then brightness distribution is improved, but excessive image conversion occurs
Solution Approach 1:
The patent dynamically adjusts the histogram processing strategy based on the detected image brightness characteristics. The system determines whether an image is entirely bright or entirely dark and automatically selects the appropriate processing mode: fixing the lower region for bright images, fixing the upper region for dark images, or performing full histogram expansion for normal images. This dynamic adaptation resolves the contradiction by ensuring histogram expansion is only applied when appropriate, preventing excessive conversion while maintaining brightness distribution quality.
3Device complexity
If conventional image conversion is used without pattern recognition, then processing is simple, but appropriate correction cannot be performed for different image characteristics
Solution Approach 1:
The patent performs preliminary classification of images into different brightness patterns (entirely bright, entirely dark, or normal) before applying conversion processing. This preliminary action enables the system to select the appropriate correction strategy for each image type, ensuring accurate correction while maintaining relatively simple processing. The classification step is computationally efficient and resolves the contradiction by enabling pattern-specific correction without significantly increasing complexity.
Data Source
AI summary
In an image data conversion device, color image data is represented in gray scale, a histogram of brightness values is created for the gray-scaled image data, it is determined based on the created histogram which image pattern of a plurality of image patterns the gray-scaled image data is classified into, a range subjected to gamma correction and a range fixed to at least one of a minimum value and a maximum value of gray scale are set for each image pattern, and image data conversion including the gamma correction is performed on the gray-scaled image data.