Document Image Background Noise Reduction via Histogram Range Pruning
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Solution Overview
Problem
Document images often suffer from background noise generated by image sensors and circuitry, which can obscure data objects and degrade image quality, and existing noise reduction techniques may improperly affect natural images or fail to differentiate between background and foreground content.
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 valley-removal and range-pruning algorithm to narrow the pixel value range, and convert selected pixel values to a uniform background color, thereby reducing background noise while preserving meaningful content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If existing noise reduction techniques are applied to document images, then background noise is reduced, but natural images or foreground content may be improperly affected or degraded
Solution Approach 1:
The patent segments the document image into background and foreground portions using connected component analysis and histogram analysis. By identifying the background as a separate connected component and analyzing its pixel value distribution, the technique applies noise reduction selectively to background regions only, preserving foreground content integrity while reducing background noise.
Solution Approach 2:
The patent applies different processing qualities to different regions of the image. The background portion receives aggressive noise reduction through pixel value replacement based on histogram analysis, while the foreground portion maintains its original quality. This local differentiation resolves the contradiction by allowing strong noise reduction where safe (background) while protecting sensitive areas (foreground).
2Object-affected harmful factors
If aggressive noise reduction is applied to reduce background noise, then background noise is reduced, but actual content may be degraded
Solution Approach 1:
The patent performs preliminary analysis of the background portion before applying noise reduction. By generating a histogram of pixel values in the background and identifying the dominant background color range, the technique prepares a safe replacement palette that preserves the essential characteristics of the background while enabling aggressive noise reduction through pixel value replacement.
Solution Approach 2:
The patent uses histogram analysis of the background portion to provide feedback on the distribution of pixel values. This feedback mechanism identifies the dominant background color and determines the appropriate replacement range, ensuring that noise reduction replaces only noisy pixel values while preserving the intended background appearance and overall image quality.
3Object-affected harmful factors
If uniform background color replacement is applied to all pixels, then background noise is reduced, but natural image variations are lost
Solution Approach 1:
The patent changes the parameter of background color from a single uniform value to a range of acceptable values based on histogram analysis. By identifying the dominant background color and its variation range, the technique replaces noisy pixel values with colors within this range rather than a single uniform color, preserving natural background variations while reducing noise.
Data Source
AI summary
A method to reduce background noise in a document image 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 a replacement range using a range pruning algorithm that narrows a range of the histogram by iteratively discarding at least one pixel value and corresponding pixel count of the histogram from at least one side of the histogram; selecting, from the connected component, at least one pixel having a corresponding pixel value within the replacement range; converting the corresponding pixel value of the at least one pixel to a uniform background color; and outputting, subsequent to the converting, the document image.