Bayer Format Image Binning with Spatially Weighted Averaging
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Solution Overview
Problem
Conventional binning processes for images in Bayer format suffer from false minutiae during color interpolation, leading to significant reduction in image quality due to the averaging method used, which does not account for spatial position relationships of pixels.
Innovation Solution
A method and device for processing images in Bayer format that perform binning by determining the position of output pixels and calculating a weighted average of selected pixels with varying weights based on their distance from the output pixel, maintaining the original pixel arrangement mode and reducing image noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional binning process uses averaging method to reduce image size, then image data volume is reduced, but image quality deteriorates due to false minutiae in color interpolation
Solution Approach 1:
The patent applies local quality by using different weights for different pixels based on their spatial position relative to the output pixel. Pixels closer to the output pixel position are assigned higher weights, while those farther away receive lower weights. This localized weighting approach preserves spatial relationships and prevents false minutiae in color interpolation, thereby maintaining image quality while achieving data reduction through binning.
Solution Approach 2:
The patent changes the parameter of pixel weighting from uniform (conventional averaging) to variable (spatially-dependent weights). By introducing spatial position as a parameter that influences the weight assigned to each pixel, the method transforms the simple averaging process into a weighted averaging process that preserves spatial relationships and improves color interpolation accuracy, thus maintaining image quality during downsampling.
2Loss of energy
If conventional binning process merges pixels to reduce image size, then transmission bandwidth is reduced, but color interpolation accuracy deteriorates
Solution Approach 1:
The patent applies local quality by assigning different weights to pixels based on their spatial proximity to the output pixel position. This localized weighting ensures that pixels contributing more accurately to the output (those closer in space) have greater influence, thereby maintaining color interpolation accuracy while achieving bandwidth reduction through pixel merging.
Solution Approach 2:
The patent changes the weighting parameter from uniform to spatially-variable, where the weight of each pixel is determined by its distance from the output pixel position. This parameter transformation preserves the spatial relationships necessary for accurate color interpolation, preventing the degradation of interpolation accuracy that occurs with simple averaging methods.
3Object-affected harmful factors
If conventional binning process performs mean value calculation, then image noise is suppressed, but spatial position relationships are lost
Solution Approach 1:
The patent applies local quality by using spatial position-dependent weights in the averaging process. This ensures that the noise suppression benefit of averaging is retained while simultaneously preserving spatial relationships, as the weighting scheme explicitly accounts for the position of each pixel relative to the output pixel.
Solution Approach 2:
The patent introduces spatial position as a parameter that modulates the weight assigned to each pixel during the mean value calculation. This parameter change transforms the simple averaging process into a weighted averaging process that suppresses noise through multiple pixel contributions while maintaining spatial fidelity through position-based weighting.
Data Source
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AI summary
A method for processing an image in Bayer format is provided. The method may include: performing a binning process in a horizontal and/or vertical direction on an image which is to be processed, so that an arrangement mode of pixels in a processed image after binning is the same with that in the image to be processed, wherein the binning process may include: determining a position of an output pixel; selecting, from the image to be processed, a plurality of pixels which have the same color component with that of the output pixel, and calculating a weighted average of the plurality of pixels, so as to obtain a pixel value of the output pixel, wherein the plurality of pixels are selected from particular positions, so that the weighted average of the plurality of pixels can be calculated. According to the present disclosure, quality of image processing can be guaranteed.