Document Image Noise Reduction via Variable Color Range Mapping
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Solution Overview
Problem
Document images often contain background noise that is difficult to distinguish from non-background content, leading to challenges in noise reduction without degrading meaningful content, especially in images with varied and complex backgrounds.
Innovation Solution
A method and system that extract a connected component corresponding to the background of a document image, generate a histogram of pixel values, apply a non-linear mapping function to create a probability distribution, and select pixels within a replacement range to convert them to a uniform background color, allowing for aggressive noise reduction in noisier backgrounds while preserving cleaner areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If aggressive noise reduction is applied to remove background noise, then background noise is reduced, but meaningful content may be degraded or removed
Solution Approach 1:
The patent applies different processing treatments to different regions of the background based on their noise characteristics. By dividing the background into multiple regions and analyzing each region's pixel value distribution separately, the system can aggressively reduce noise in high-noise regions while applying gentler processing or no processing to low-noise regions that contain meaningful content, thus resolving the contradiction between noise reduction and content preservation
Solution Approach 2:
The patent dynamically adjusts the noise reduction parameters based on the statistical analysis of pixel value distributions in different background regions. By calculating histograms and identifying peak values for each region, the system adapts the replacement range and processing intensity to match the actual noise levels, allowing aggressive reduction where needed while preserving content in cleaner areas
2Device complexity
If a fixed replacement range is used for noise reduction, then processing is simple, but it cannot adapt to varying noise levels in different background regions
Solution Approach 1:
The patent segments the background into multiple regions and performs independent statistical analysis on each segment. This segmentation allows the system to capture the varying noise characteristics across different parts of the image, with each region getting its own optimized replacement range based on its specific pixel value distribution, thereby achieving adaptability without excessive complexity
Solution Approach 2:
The system performs self-adjustment by automatically calculating the histogram and identifying peak values for each background region, then using these statistics to determine the appropriate replacement range. This self-service approach eliminates the need for manual parameter tuning or complex external control systems, achieving adaptability through automated local analysis
Data Source
AI summary
A method to reduce background noise in a document image. The method includes extracting, from the document image, a connected component corresponding to a background of the document image, generating a histogram of pixel values of the connected component, generating, using a non-linear mapping function based on the histogram, a non-linear probability distribution of the pixel values in the connected component, generating, based at least on a comparison between the non-linear probability distribution and a predetermined threshold, a replacement range of the pixel values, selecting, from the connected component, a pixel having a pixel value within the replacement range, and converting the pixel value of the pixel to a uniform background color.