Preferred Color Correction in LCDs via LCH Segmentation
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Solution Overview
Problem
Conventional preferred color correction methods in image display devices suffer from contour noise and deteriorated luminance due to inadequate brightness correction, and limited capability in considering the contents of the input image.
Innovation Solution
A method and apparatus that convert input image data into lightness (L), chroma (C), and hue (H) data, detect preferred-color pixels, calculate average values, and correct C and H data based on differences with reference values, while adjusting L data specifically for skin-color pixels, using best linear estimation and weighting functions to prevent contour noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the area correcting method is used to correct preferred color, then the preferred-color area can be detected and converted to user-preferred color, but contour noise occurs and luminance deteriorates because brightness is not corrected
Solution Approach 1:
The patent segments the color correction process into three distinct components: chroma correction (C data), hue correction (H data), and lightness correction (L data). This segmentation allows each component to be optimized independently, preventing the contour noise and luminance deterioration that occur when only chroma and hue are corrected without addressing lightness separately.
Solution Approach 2:
The patent applies different correction strategies to different regions of the image based on local characteristics. Specifically, it detects preferred-color pixels and applies targeted correction only to those regions while preserving other areas, and uses weighting functions to apply different correction intensities at different locations, thereby preventing contour noise at boundaries.
2Measurement precision
If the point correcting method is used to correct preferred color, then one target color can be positioned, but preferred color correction capability deteriorates because the contents of the input image are not considered
Solution Approach 1:
The patent transforms the static point-correction approach into a dynamic system that adapts to image contents. It detects preferred-color pixels based on their actual color values and applies corrections tailored to each detected region, making the correction capability adaptive rather than fixed to a single target point.
Solution Approach 2:
The patent changes the correction parameters (chroma, hue, and lightness values) based on the detected preferred-color pixel characteristics and their deviation from reference values. This allows the system to adjust correction strength and parameters dynamically according to the specific image content and color differences, rather than applying a fixed transformation.
Data Source
AI summary
A method and apparatus for correcting a preferred color, which is capable of correcting the preferred color in consideration of an input image and the visual characteristics of a person by correcting differences between colors preferred by the person and an average color coordinate of a color to be corrected in the input image, and a liquid crystal display device using the same are disclosed. The method for correcting a preferred color includes converting data of an input image into lightness (L), chroma (C) and hue (H) data, detecting a preferred-color pixel from the input image, calculating average values of the L, C and H data of the preferred-color pixel, correcting the C and H data of the preferred-color pixel according to differences between the average values of the C and H data and reference values of the C and H data, correcting the L data of the preferred-color pixel according to the average value of the L data according to the hue of the preferred-color pixel, and inversely converting the corrected L, C and H data into image data.