Image Acquisition Apparatus Space-Variant Grayscale Conversion
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Solution Overview
Problem
Existing image-acquisition apparatuses generate unnatural grayscale characteristics in uniform portions with minute luminance gradients due to uniform grayscale conversion, leading to unnatural emphasis of luminance gradients in images.
Innovation Solution
An image-acquisition apparatus that performs space-variant grayscale conversion by calculating and adjusting correction coefficients for each pixel region, using a combination of image processing units, correction-coefficient calculating and adjusting parts, and a grayscale converter to ensure natural luminance gradients across the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If space-variant grayscale conversion is performed on uniform portions with minute luminance gradients, then grayscale depth increases, but unnatural emphasis of luminance gradients occurs
Solution Approach 1:
The patent applies different grayscale conversion strategies to different image regions based on their local characteristics. For uniform portions with minute luminance gradients, the patent detects these regions and applies a conversion method that preserves the subtle gradients, while for non-uniform portions, it applies conventional space-variant grayscale conversion. This local differentiation resolves the contradiction by adapting the conversion approach to the specific needs of each region.
Solution Approach 2:
The patent dynamically adjusts the grayscale conversion process based on local image characteristics. By calculating luminance gradients and detecting uniform portions, the system adaptively selects appropriate conversion methods for different regions. This dynamic approach allows the system to increase grayscale depth where needed while avoiding unnatural emphasis in uniform areas.
2Manufacturing precision
If histogram smoothing is applied in uniform portions, then grayscale conversion is improved, but unnatural grayscale characteristics are generated
Solution Approach 1:
The patent applies histogram smoothing selectively only in non-uniform portions of the image, while avoiding its application in uniform portions with minute luminance gradients. By detecting the local characteristics of each region, the system applies appropriate processing - histogram smoothing where it benefits the image, and preservation of original characteristics in uniform areas - thus resolving the contradiction between improvement and naturalness.
3Manufacturing precision
If different grayscale conversion is performed in each region, then image quality improves for high contrast scenes, but processing complexity increases
Solution Approach 1:
The patent segments the image into different regions based on local characteristics such as luminance gradient magnitude. By dividing the image into uniform and non-uniform portions, the system can apply simplified processing to uniform areas and more sophisticated processing to non-uniform areas, reducing overall computational complexity while maintaining image quality.
Solution Approach 2:
The patent applies full space-variant grayscale conversion only to non-uniform portions of the image, while using a simpler preservation approach for uniform portions. This partial application of the complex algorithm reduces processing complexity while maintaining the quality benefits where they are most needed.
Data Source
AI summary
An image-acquisition apparatus is provided, including a correction-coefficient calculating unit 109 for obtaining an image signal subjected to prescribed image processing and creating, in each region, a first correction-coefficient group formed of a plurality of correction coefficients corresponding to a plurality of pixels; a correction-coefficient-group adjusting unit 110 for creating a second correction-coefficient group by adjusting the first correction-coefficient group using the image signal from an image-acquisition device or a feature of the image signal subjected to the image processing; and a grayscale converter 111 for performing grayscale conversion processing in each region using the second correction-coefficient group.