Image Edge Processing via Bilateral Filtering
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Solution Overview
Problem
Low-cost digital cameras and camcorders often produce images with noise and distortions due to insufficient optical resolution and electrical noise, leading to reduced image quality.
Innovation Solution
A system comprising an edge filter, an edge-smoothing filter, and an adder that processes image edges to reduce noise and enhance clarity, using high-pass and band-pass filters to preserve edges and smooth noise, with an optional gain amplifier and limiter to optimize image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If low-cost optics or electronics are used in digital cameras, then the cost is reduced, but image quality deteriorates due to image noise and distortions
Solution Approach 1:
The patent applies bilateral filtering to convert the harmful image noise into beneficial edge-smoothed data by selectively preserving edge information while removing noise. The filter uses intensity difference calculations to distinguish between noise and actual image edges, transforming the noise problem into an opportunity to enhance image quality without increasing hardware cost.
Solution Approach 2:
The patent changes the processing parameters by applying different filtering operations to different regions of the image. The edge filter and bilateral filter operate with specific parameter settings (kernel size, sigma values) that adapt to local image characteristics, allowing noise reduction while preserving edges in cost-effective post-processing.
2Object-affected harmful factors
If traditional noise filtering methods are applied, then image noise is reduced, but image edges become blurred and image clarity deteriorates
Solution Approach 1:
The patent applies local quality by using bilateral filtering that adapts to local image characteristics. The filter calculates intensity differences locally and applies different filtering strengths to different regions: strong noise reduction in uniform areas and minimal filtering at edge locations. This local adaptation preserves image clarity while reducing noise effectively.
Solution Approach 2:
The patent segments the image processing into distinct stages: edge detection, edge smoothing with bilateral filtering, and final combination. This segmentation allows different processing strategies to be applied to different parts of the image, preserving edges while removing noise without blurring overall image clarity.
3Object-affected harmful factors
If aggressive edge smoothing is applied to remove noise, then image noise is reduced, but image sharpness and perceived clarity deteriorate
Solution Approach 1:
The patent applies dynamics by making the filtering operation adaptive rather than static. The bilateral filter dynamically adjusts its behavior based on local intensity variations, applying strong smoothing where appropriate and preserving sharpness where edges are detected. This dynamic adaptation maintains both noise reduction and image sharpness.
Solution Approach 2:
The patent uses feedback mechanisms where the filtered output is combined with the original image data through addition. The edge-smoothed data is added back to the original image, providing feedback that preserves original sharpness information while incorporating noise reduction benefits, thereby maintaining both low noise and high sharpness.
Data Source
AI summary
A system and method for processing an image edge includes an edge filter that processes an image input to generate edge data. An edge-smoothing filter processes the edge data to filter-out image noise and preserve the image edge, thus generating edge-smoothed data. An adder adds the edge-smoothed data to the image input, thus generating an edge-smoothed image.