Display Driver Pixel-Specific Characterization for Contrast Enhancement
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Solution Overview
Problem
Current auto contrast enhancement techniques for panel display devices, such as liquid crystal display devices, often result in 'blocked up shadows' in dark regions and 'clipped white' in bright regions due to uniform correction calculations across the entire image, leading to reduced grayscale representation and potential block noise at area boundaries.
Innovation Solution
A display device and method that calculates area characterization data for defined regions and generates pixel-specific characterization data by filtering area characterization data from adjacent areas, allowing for individual pixel corrections based on localized image features to enhance contrast without causing block noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If uniform correction calculation is performed across the entire image, then contrast enhancement is achieved, but blocked up shadows and clipped white occur reducing grayscale representation
Solution Approach 1:
The image is divided into multiple regions based on luminance characteristics, and contrast correction is performed separately for each region. This segmentation allows different correction parameters to be applied to different areas, preventing the loss of grayscale representation while achieving contrast enhancement in each specific region.
Solution Approach 2:
Different correction parameters are applied to different regions of the image based on their local luminance characteristics. Dark regions receive different correction treatment than bright regions, allowing contrast enhancement without causing blocked up shadows or clipped white, thus preserving grayscale representation in each local area.
2Illumination intensity
If contrast correction is performed for each area individually, then local contrast enhancement is achieved, but block noise occurs at area boundaries
Solution Approach 1:
Adjacent regions share common boundary pixels that are used by both regions for correction calculation. This merging approach ensures continuity at region boundaries and eliminates the abrupt transitions that cause block noise, while still maintaining local contrast enhancement characteristics.
3Illumination intensity
If strong contrast enhancement is performed, then image contrast is improved, but the number of representable grayscale levels is reduced
Solution Approach 1:
The correction parameters are dynamically adjusted based on the local luminance characteristics of each region. By changing the correction strength parameter according to regional luminance conditions, the system achieves strong contrast enhancement where needed while preserving grayscale levels in other regions, thus preventing information loss.
Data Source
AI summary
A display device includes a display panel including a display region and a driver driving each pixel of the display region in response to input image data. The driver calculates area characterization data indicating feature quantities of an image displayed in each of areas defined in the display region for each of the areas, based on the input image data and generates pixel-specific characterization data associated with each pixel by applying filtering to the area characterization data associated with the area in which each pixel is located and with areas adjacent to the area in which each pixel is located. The driver generates output image data associated with each pixel by performing a correction on the input image data associated with each pixel in response to the pixel-specific characterization data associated with each pixel and drives each pixel in response to the output image data associated with each pixel.