Algorithm Modification for Image Edge-Checking Optimization
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Solution Overview
Problem
Existing image processing algorithms consume significant computing resources due to the need for edge-checking operations, especially when processing large images like high-definition videos, as they must verify the validity of input pixels relative to the image edges, which becomes inefficient with millions of pixels.
Innovation Solution
An algorithm modification machine identifies regions within an output image where edge-checking is unnecessary and generates a modified version of the image modification algorithm that omits edge-checking operations, using a pixel offset to determine valid input pixels for generating output pixels within these regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If edge-checking operations are performed for all pixels in the image, then the validity of input pixels is ensured, but computing resource consumption increases significantly
Solution Approach 1:
The patent applies local quality by differentiating the processing requirements for different regions of the output image. Interior pixels use a simplified algorithm without edge-checking, while boundary pixels use the full algorithm with edge-checking. This allows the system to maintain reliability where needed (at boundaries) while reducing computing resource consumption in the interior regions where edge-checking is unnecessary.
2Reliability
If edge-checking operations are performed for all pixels, then input pixel validity is verified, but processing time increases
Solution Approach 1:
The patent implements local quality by applying different processing methods to different spatial regions. Interior pixels are processed using an optimized path that skips edge-checking operations, while only boundary pixels undergo the time-consuming edge-checking verification. This significantly reduces overall processing time while maintaining reliability for pixels where edge-checking is actually necessary.
3Use of energy by moving object
If a modified algorithm without edge-checking is used, then computing resource consumption decreases, but input pixel validity may be compromised
Solution Approach 1:
The patent resolves this contradiction by applying local quality through spatial differentiation of algorithm application. The modified algorithm without edge-checking is applied specifically to interior pixels where validity is guaranteed by position, while the original algorithm with edge-checking is retained for boundary pixels where validity must be verified. This ensures reliability is maintained where needed while achieving computing resource savings.
Solution Approach 2:
The patent applies segmentation by dividing the output image into two distinct regions: interior pixels and boundary pixels. Each region is processed using the most appropriate algorithm variant - the simplified version for interior pixels and the full version for boundary pixels. This segmentation allows the system to optimize computing resources while maintaining overall reliability.
4Reliability
If the full algorithm with edge-checking is applied to all pixels, then input pixel validity is ensured, but device complexity increases
Solution Approach 1:
The patent applies local quality by implementing a hybrid approach where the algorithm structure is simplified for interior pixels and maintained in full for boundary pixels. This reduces the effective complexity of the processing system for the majority of pixels while preserving the complete validation capability where spatial position requires it.
Data Source
AI summary
An analysis module accesses an input image, identifies an algorithm to be used to generate an output image from the input image, analyzes the algorithm, and determines a pixel offset of the algorithm. A generation module identifies a region of the output image in which output pixels are to be generated without an edge-checking operation. The generation module generates a modified version of the algorithm that omits the edge-checking operation and generates the output image by using the modified version to generate output pixels in the identified region.