Texture Mask Image Adjustment for Contrast Enhancement
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Solution Overview
Problem
Digital images often suffer from reduced brightness range due to lower dynamic range, leading to lost details in shadows or washed-out light areas, making it challenging to improve contrast effectively without amplifying noise.
Innovation Solution
A method that detects texture regions in images using wavelet-based filters and generates a mask to selectively apply adjustment operations, such as local contrast enhancement, to enhance image quality by distinguishing between high-detail and low-detail areas, thereby avoiding noise amplification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If local contrast enhancement is applied to the entire image, then image contrast is improved, but noise is amplified in non-texture regions
Solution Approach 1:
The patent applies local contrast enhancement selectively based on texture detection. A mask is generated that identifies texture regions (where enhancement is desirable) versus non-texture regions (where enhancement would amplify noise). The contrast enhancement operation is then applied with spatially varying strength controlled by the mask, achieving local quality differentiation.
2Object-generated harmful factors
If manual editing is used to selectively adjust contrast regions, then noise amplification is avoided, but editing time and effort increase
Solution Approach 1:
The system performs automatic texture detection and mask generation without requiring manual user intervention. The algorithm autonomously identifies texture regions, generates the appropriate mask, and applies contrast enhancement selectively, making the system self-sufficient and eliminating time-consuming manual editing while avoiding noise amplification.
Solution Approach 2:
The patent transforms the image into a texture map by detecting texture strength at each pixel location. This parameter transformation creates a mask that automatically distinguishes between regions suitable for contrast enhancement and those that are not, enabling automated selective processing without manual input.
Data Source
AI summary
Implementations relate to adjusting images using a texture mask. In some implementations, a method includes detecting one or more texture regions having detected texture in an image, and generating a mask from the image based on the detected texture regions. The detected texture regions are distinguished in the mask from other regions of the image that do not have detected texture. The method applies one or more adjustment operations to the image in amounts based on values of the mask.