Image Sensor Texture Analysis for Resolution Speed Trade-off
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Image sensing devices face a loss of resolution performance in low light modes or preview modes, as existing technologies fail to effectively analyze and process image textures to maintain image quality.
Innovation Solution
An image sensing device with an analysis module, sum module, and processing module that calculates weights based on pixel values to generate target sum values, distinguishing between edge and flat regions, thereby improving image resolution by applying texture characteristics in specific modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If pixel values are summed without applying texture characteristics, then processing speed is improved, but resolution performance is lost
Solution Approach 1:
The patent applies different processing methods to different regions based on texture characteristics. Edge regions use weighted summation with calculated weights to preserve resolution, while flat regions use simple summation for speed. This local differentiation resolves the contradiction by applying the appropriate processing method to each region rather than using a uniform approach.
Solution Approach 2:
The system dynamically adjusts the processing method based on real-time texture analysis. The image processor determines whether to apply weighted summation or simple summation based on the detected texture type (edge or flat region), making the processing approach adaptive rather than fixed, thus optimizing both speed and resolution performance.
2Measurement precision
If texture characteristics are applied to all regions, then resolution performance is maintained, but processing complexity increases
Solution Approach 1:
Instead of applying complex texture-based processing uniformly across the entire image, the patent identifies specific regions (edge regions vs. flat regions) and applies appropriate processing methods only where needed. This reduces overall processing complexity while maintaining resolution performance in critical areas.
Solution Approach 2:
The patent applies texture characteristic analysis and weighted summation only to edge regions where it is necessary for maintaining resolution, while using simpler processing for flat regions. This partial application of complex processing only where needed reduces overall system complexity while preserving resolution performance.
3Speed
If simple summation is used, then processing speed is improved, but image quality deteriorates in edge regions
Solution Approach 1:
The patent distinguishes between edge regions and flat regions, applying weighted summation with texture-based weights to edge regions to maintain image quality, while using simple summation for flat regions to maintain processing speed. This local differentiation resolves the contradiction by matching the processing method to the specific regional requirements.
Data Source
AI summary
An image sensing device includes an analysis module suitable for analyzing, based on pixel values of a kernel, an image texture of the kernel including a target pixel group and one or more adjacent pixel groups, a sum module suitable for generating any one of a first target sum value and a second target sum value based on an analysis result of the analysis module, wherein first target sum value is obtained by applying texture characteristics of the kernel in target pixel values of the target pixel group and the second target sum value is obtained without applying the texture characteristics of the kernel in the target pixel values, and a processing module suitable for generating a sum image based on any one of the first and second target sum values.