Image Processing Brightness Correction for Noise Reduction and Contour Clarity
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Solution Overview
Problem
Existing image processing technologies often blur the contour of objects in images while reinforcing noise on plane parts, failing to effectively balance noise reduction and contour emphasis.
Innovation Solution
An image processing apparatus and method that classify brightness change levels using threshold values and calculate dynamic weights to correct pixel brightness, minimizing noise on plane parts while emphasizing image contours.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Shape
If a sharpening filter is used to emphasize image contour, then the contour clarity is improved, but noise on plane parts is reinforced
Solution Approach 1:
The patent applies different processing strengths to different regions of the image. Edge parts receive stronger sharpening processing while plane parts receive weaker processing. This is achieved by calculating a weight value based on edge detection results and using this weight to control the degree of sharpening applied to each pixel, thereby locally adapting the processing strength to the image content.
Solution Approach 2:
The patent dynamically adjusts the sharpening strength based on the local image characteristics. Instead of using a fixed sharpening filter, the system calculates edge information and adapts the processing parameters in real-time. The weight value is dynamically computed based on the detected edges, allowing the sharpening effect to vary across different regions of the image.
2Measurement precision
If sharpening processing is applied to emphasize contours, then image definition is improved, but noise is generated and reinforced on plane parts
Solution Approach 1:
The patent applies different processing strengths to different regions of the image. Edge parts receive stronger sharpening processing while plane parts receive weaker processing. This is achieved by calculating a weight value based on edge detection results and using this weight to control the degree of sharpening applied to each pixel, thereby locally adapting the processing strength to the image content.
Solution Approach 2:
The patent converts the harmful noise generation effect into a beneficial edge enhancement effect. By detecting edges and applying sharpening selectively in those regions, the system amplifies the useful edge information while suppressing the harmful noise in plane areas. The edge detection mechanism allows the system to distinguish between meaningful image features and noise, applying processing only where beneficial.
Data Source
AI summary
An image processing apparatus is provided, including a brightness change level classifying unit, a dynamic weight calculating unit, and a brightness correcting unit. The brightness change level classifying unit compares a brightness change average value representing brightness changes from a pixel of interest to neighboring pixels around the pixel of interest with an upper threshold value and a lower threshold value and classifies the brightness change level of the pixel of interest into three types of levels according to the result of the comparison. An upper threshold value and a lower threshold value are predetermined based on the brightness of the pixel of interest. The dynamic weight calculating unit calculates different dynamic weights according to the brightness change level of the pixel of interest. The brightness correcting unit corrects the brightness of the pixel of interest, based on the dynamic weights. Accordingly, noise generated on a plane part of an image is minimized and a contour of the image is appropriately emphasized, consequently improving the definition of images.