Image Pixelization via Mosaic Mapping for Real-Time Processing
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Solution Overview
Problem
Current methods for image pixelization, whether implemented on GPU or CPU, consume significant computational resources due to the need for calculating average color values for each mosaic tile, leading to high workload on CPU and GPU.
Innovation Solution
A method and system that utilize a mosaic mapping table to transform input images into pixelated images by manipulating pixel coordinates, eliminating the need for calculating average color values and leveraging dedicated circuitry for transformation, thus reducing the burden on CPU and GPU.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPU or CPU is used to calculate average color values for each mosaic tile, then pixelization quality is improved, but computational resource consumption increases
Solution Approach 1:
The patent pre-calculates and stores the mapping relationships between original image pixels and pixelated image pixels in a mapping table before actual pixelization processing. This preliminary action allows the system to avoid repeated complex calculations during runtime, significantly reducing computational resource consumption while maintaining pixelization quality
Solution Approach 2:
The patent creates a mapping table that copies and stores the coordinate transformation relationships between input and output images. Instead of performing complex average color calculations for each tile during processing, the system uses this pre-copied mapping data to directly determine pixel values, reducing computational load while preserving pixelization effects
2Measurement precision
If average color value calculation is performed for each pixel block, then pixelization accuracy is improved, but processing time increases
Solution Approach 1:
The mapping table is generated in advance, storing all coordinate transformations needed for pixelization. During actual processing, the system only needs to lookup pre-computed values rather than performing time-consuming average color calculations for each tile, significantly reducing processing time while maintaining accuracy
Solution Approach 2:
The patent introduces a mapping table as an intermediary data structure between the input image and output pixelated image. This intermediary stores pre-computed coordinate relationships, allowing the system to avoid direct complex calculations during processing and thereby reducing processing time while preserving pixelization accuracy
3Speed
If dedicated circuitry is used for pixelization transformation, then processing speed is improved, but device complexity increases
Solution Approach 1:
The patent replaces the software-based pixelization processing (which would require complex CPU/GPU computations) with a dedicated hardware circuit implementation. This hardware circuit directly implements the coordinate transformation and pixel value copying operations defined by the mapping table, achieving high-speed real-time processing while the complexity is encapsulated in the hardware design rather than software algorithms
Data Source
AI summary
Provided is a pixelization method. The method involves generating a mosaic mapping table. The mosaic mapping table includes multiple mapping entries, each mapping entry recording an output pixel coordinate of a pixelated image and an input pixel coordinate of an input image. The method further involves using the mosaic mapping table to transform the input image into the pixelated image. The output pixel value corresponding to the output pixel coordinate in each mapping entry is set to the input pixel value corresponding to the input pixel coordinate in that mapping entry.