Macro Sigma Filter for Flat Region Image Smoothing
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Solution Overview
Problem
Conventional sigma filters are inefficient in smoothing flat image regions due to high computational complexity and memory requirements, and they often lose high-contrast edges when increasing filtering strength.
Innovation Solution
The introduction of a macro sigma filter that uses block average pixel values to identify flat regions and applies a weighted average only when pixel values differ by less than a sigma value, reducing memory requirements and computational complexity by applying the filter selectively within flat regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the sigma value is increased to increase filtering strength, then noise reduction is improved, but high-contrast edges are smoothed and lost
Solution Approach 1:
The patent applies different filtering strengths to different regions of the image. By detecting flat regions using gradient magnitude thresholds, the filter applies stronger smoothing (higher sigma value) to flat areas while maintaining original values in edge regions, thus achieving local adaptation of filtering intensity.
2Manufacturing precision
If the filter kernel size is increased to improve filtering effectiveness, then noise reduction is improved, but computational complexity increases
Solution Approach 1:
The patent segments the image processing task by first identifying flat regions using gradient magnitude calculations, then applying filtering only within those segmented regions. This segmentation approach reduces the overall computational burden by limiting the filter's operational scope to only those pixels that require smoothing.
Solution Approach 2:
The patent applies partial action by selectively filtering only flat regions rather than the entire image. By using gradient magnitude to identify regions that need filtering and leaving edge regions unfiltered, the computational complexity is reduced while maintaining filtering effectiveness where needed.
3Manufacturing precision
If conventional sigma filter is applied to flat regions, then noise reduction is achieved, but computational load and memory requirements are excessively high
Solution Approach 1:
The patent makes the filtering operation local to flat regions only, determined by gradient magnitude thresholds. This local application of the sigma filter reduces both computational load and memory requirements by processing only the necessary pixels rather than the entire image.
Solution Approach 2:
The patent applies partial action by filtering only flat regions identified through gradient analysis. This selective filtering approach reduces computational load and memory usage by avoiding redundant processing in edge regions where filtering would not be beneficial.
Data Source
AI summary
An image filter and method of smoothing pixel values. A pixel value of a pixel to be smoothed is compared with block average pixel values of each of a plurality of pixel blocks. The pixel to be smoothed may be downstream from each of the pixel blocks. If the difference between the pixel value and each of the block average pixel values is less than a corresponding sigma threshold value for each of the pixel blocks, a first sigma filter utilizing the block average pixel values is applied to the pixel to be smoothed. If the difference between the pixel value and any one of the block average pixel values is not less than a corresponding sigma threshold value, a second sigma filter is applied to the pixel to be smoothed.