Image Processing System Weighted Pixel Combination
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Solution Overview
Problem
Existing image processing systems fail to produce clear images when pattern matching between infrared and visible-light image data is unsuccessful, often resulting in fully whitened or fully blackened spots, which prevents the combination of infrared and visible-light image data to form a clear image.
Innovation Solution
An image processing system that applies weights to pixel values within specific threshold ranges of both visible-light and near-infrared image data, dividing them into spatial frequency bands for weighted combination, thereby reducing the likelihood of fully whitened or blackened spots and ensuring a clear image output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pattern matching is used to extract infrared image data corresponding to objects, then object identification accuracy is improved, but when pattern matching fails, fully whitened or blackened spots occur and clear images cannot be produced
Solution Approach 1:
The patent applies preliminary weighting to pixel values based on threshold ranges before combining infrared and visible-light images. By pre-adjusting pixel values within specific luminance ranges, the system prevents overexposure (fully whitened spots) and underexposure (fully blackened spots) that occur when pattern matching fails, ensuring reliable image quality regardless of pattern matching success.
2Illumination intensity
If infrared image data is substituted for visible-light image data through combining operation, then night vision capability is improved, but when infrared data cannot be extracted, the visible-light image data becomes fully whitened or blackened
Solution Approach 1:
The patent applies different weighting strategies to different regions of the image based on local pixel luminance characteristics. By dividing pixels into different luminance ranges and applying appropriate weights to each range, the system maintains local image quality in each region, preventing global degradation to fully whitened or blackened images when infrared data extraction fails.
3Reliability
If weighted combination of pixel values from visible-light and near-infrared images is applied, then image clarity is improved, but system complexity increases due to multiple processing steps
Solution Approach 1:
The patent changes the parameter of pixel luminance values by applying weights based on threshold ranges. This parameter transformation converts raw pixel values into adjusted values that inherently prevent overexposure and underexposure, achieving clear images through a systematic parameter modification approach rather than complex multi-stage processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively produces clear images by weighting pixel values across spatial frequency bands, excluding unwanted light influences and ensuring accurate luminance capture, resulting in high visibility and reliability, even in conditions with limited dynamic range.
Implementation Method 1
the near-infrared irradiator is configured to irradiate the object with near-infrared rays
Implementation Method 2
the second image pickup device may be configured to demodulate the near-infrared rays reflected by the object, and capture the near-infrared image from the demodulated near-infrared rays
Data Source
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AI summary
An image processing system includes a first image pickup device (110), a near-infrared irradiator (120A), a second image pickup device (120B), and a signal processor (130; 200). The signal processor (130; 200) is configured to: apply a first weight to the first pixel value when the signal processor (130; 200) determines that the first pixel value is within the first range; apply a second weight to the second pixel value when the signal processor (130; 200) determines that the second pixel value is within the second range; and calculate a fifth pixel value as a pixel value of each pixel of a composite image into which the visible-light image and the near-infrared image are combined, based on a third pixel value obtained by applying the first weight to the first pixel value, and a fourth pixel value obtained by applying the second weight to the second pixel value.