Pixel Binning for Even Optical Center Distribution
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Solution Overview
Problem
High pixel resolution in image sensors leads to increased image data processing demands, requiring higher speed and capacity, while reducing pixel resolution for video recording and sensitivity improvement results in poor image quality due to data reduction methods like pixel binning.
Innovation Solution
A method for reducing digital image resolution by binning pixels such that their optical centers remain evenly distributed, using a color mask with specific pixel selection and rotation to generate macro pixels, thereby maintaining image quality and reducing data without significant loss of detail.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel resolution is increased to improve image quality, then image quality is improved, but data processing demands and memory capacity requirements increase
Solution Approach 1:
The patent combines multiple pixels into macro pixels by selecting pixels at specific relative positions (including diagonal positions) and merging their values. This merging reduces the total number of pixels and data amount while maintaining image quality through proper spatial distribution of macro pixel optical centers.
2Quantity of substance
If pixel binning is used to reduce data amount, then data amount is reduced, but image quality deteriorates due to poor distribution of optical centers
Solution Approach 1:
The patent applies local quality by selecting pixels at specific local positions within each macro pixel group, including diagonal positions. This ensures that optical centers of macro pixels are evenly distributed across the image, preventing clustering and maintaining image quality while reducing data amount.
Solution Approach 2:
The patent extends pixel selection to diagonal dimensions by including pixels at diagonal relative positions in addition to horizontal and vertical positions. This multi-dimensional selection approach ensures uniform spatial distribution of macro pixel optical centers, preventing clustering artifacts.
3Quantity of substance
If every second or third pixel is read out to reduce data amount, then data amount is reduced, but image quality becomes poor
Solution Approach 1:
Instead of skipping pixels, the patent merges values of multiple pixels (including diagonally positioned ones) to form macro pixel values. This combining approach preserves image information while reducing data amount, avoiding the quality degradation associated with pixel skipping methods.
Data Source
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AI summary
The invention relates to a method for reducing the pixel resolution of a digital image by binning pixels together to form macro pixels. The digital image comprises pixels arranged in a colour mask of at least three different colours. The colour mask can be a Bayer mask comprising one red pixel, two green pixels and one blue pixel. The pixel binning method comprises selecting a number of pixels of each colour. For example, in order to obtain a factor two resolution reduction, four red pixels can be binned for generating a red macro pixel and eight green pixels can be binned for generating two green macro pixels. By selecting for example only one blue pixel and using that pixel for generating a blue macro pixel the optical centres of the macro pixels will be evenly distributed over the image.