Adaptive Edge Sharpening for Noise-Aware Image Processing
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Solution Overview
Problem
Existing edge sharpening techniques amplify noise in images, leading to deteriorated image quality when applied to images containing noise.
Innovation Solution
An image processing apparatus and method that adjusts the gain weight for edge sharpening by considering the similarity between each pixel and its surrounding pixels, applying a larger weight to pixels with higher similarity and lower complexity, and using a band-pass filter to remove noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a gain is applied to pixels corresponding to a boundary for edge sharpening, then the boundary between object and background becomes clear, but noise is amplified
Solution Approach 1:
The patent applies different gain weights to different pixels based on local image characteristics. By calculating the standard deviation of pixel values in a local neighborhood, the system determines whether each pixel lies on an edge or in a noise region, and applies appropriate gain accordingly. This local differentiation allows edge enhancement while suppressing noise amplification.
Solution Approach 2:
The patent dynamically adjusts the gain parameter for each pixel based on local statistical properties (standard deviation). Instead of applying a uniform gain, the system modifies the gain parameter locally according to the calculated noise level and edge strength, achieving adaptive edge sharpening that prevents noise amplification.
2Measurement precision
If edge sharpening is applied to enhance image sharpness, then boundaries become clearer, but image quality deteriorates due to noise
Solution Approach 1:
The system evaluates local image characteristics (standard deviation of pixel values) to distinguish between genuine edges and noise regions. By applying quality-aware gain adjustment locally, it enhances sharpness at true boundaries while maintaining reliability in noise-prone areas.
Solution Approach 2:
The patent uses local statistical feedback (standard deviation calculation) to control the gain application. The calculated standard deviation provides feedback about the local noise level, which then modulates the gain parameter to prevent noise amplification while maintaining edge enhancement where appropriate.
Data Source
AI summary
An image processing apparatus includes an input device configured to receive an image, an image processor configured to enhance a sharpness of the image, and an output device configured to output the image with the enhanced sharpness, where the image processor is further configured to determine a weight of a gain for each pixel included in an edge area of the image based on a similarity between each pixel and adjacent pixels and apply a modified gain, which reflects the determined weight, to each pixel included in the edge area of the image.