Image Processing Apparatus Visibility Enhancement Color Gamut Control
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Solution Overview
Problem
Existing image processing technologies face challenges in enhancing visibility and color adjustment of skin regions in images without causing color values to fall outside the color gamut, particularly in color spaces like CIE Lab, which can result in unnatural colors and gradation inversion.
Innovation Solution
An image processing apparatus that includes a skin-region detection unit, equivalent color-space converter, representative chromaticity calculation unit, visibility processing unit, color adjustment unit, and color-space inverse converter, which generates a first image by enhancing visibility in the HSV color space and adjusts chromaticity in the CIE Lab color space to prevent color gamut issues and gradation inversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If visibility enhancement process is performed in CIE Lab color space, then visibility of subject is enhanced, but color values fall outside color gamut causing unnatural colors and gradation inversion
Solution Approach 1:
The patent segments the image processing into two distinct parts: (1) visibility enhancement in HSV color space where only the Luminance channel is processed, and (2) chromaticity adjustment in CIE Lab color space where only the a* and b* channels are processed. This segmentation prevents the color values from falling outside the color gamut while still achieving visibility enhancement.
Solution Approach 2:
The patent introduces HSV color space as an intermediary for the visibility enhancement process. Instead of directly enhancing visibility in CIE Lab color space (which causes color gamut issues), the patent uses HSV as a mediator to perform luminance enhancement, then transitions to CIE Lab for chromaticity adjustment, thus avoiding the harmful effects while achieving the desired outcome.
2Illumination intensity
If color values are adjusted to enhance visibility, then subject visibility is improved, but color naturalness deteriorates due to color gamut violations
Solution Approach 1:
The patent applies different processing qualities to different aspects of color: the Luminance channel in HSV space is enhanced for visibility, while the chromaticity channels (a* and b* in CIE Lab) are carefully adjusted to maintain natural colors. This local differentiation of processing quality ensures visibility improvement without compromising color naturalness.
Solution Approach 2:
The patent changes the parameter space for different processing goals: uses Luminance parameter in HSV space for visibility enhancement, and carefully controls the a* and b* chromaticity parameters in CIE Lab space to maintain color naturalness. This strategic parameter selection and adjustment resolves the contradiction between visibility and color naturalness.
3Illumination intensity
If visibility enhancement is performed on entire image, then overall visibility is improved, but processing complexity increases
Solution Approach 1:
The patent applies local quality by performing visibility enhancement on the entire image in HSV space (affecting only the Luminance channel), then applies selective chromaticity adjustment in CIE Lab space. This approach improves overall visibility efficiently while maintaining color accuracy, balancing processing complexity with effectiveness.
Data Source
AI summary
An image processing apparatus includes a first-image generation unit that generates a first image by performing a visibility enhancement process on an original image in a first color space that is a color space not prone to having color values falling outside a color gamut as a result of conversion of color values of pixels in the original image in the visibility enhancement process, a representative chromaticity determination unit that determines a representative chromaticity that represents chromaticities of pixels in a first region that is an entirety or a part of one of the original image and the first image, and a second-image generation unit that generates a second image by performing, in a second color space, a process for adjusting color values of pixels in a second region that is the entirety or the part of the first image to make the representative chromaticity close to a target chromaticity.