Geometric Shape Detection for Image Encoding Complexity Reduction
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Solution Overview
Problem
Current image processing technologies require high processing complexity and performance from encoding-side devices, which increases the demand for resources and complicates the transmission of images, especially as users seek higher quality image services.
Innovation Solution
The method involves a server determining geometric shapes in an image and generating indication information based on similarity thresholds, allowing the decoding-side device to reconstruct images without the need for complex processing by the encoding-side device, thereby reducing the processing complexity and performance requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If complex image compression processing is performed by the encoding-side device, then image quality and bandwidth adaptation are improved, but processing complexity and performance requirements increase
Solution Approach 1:
The image is divided into multiple image units, and geometric shapes are detected and recognized in each image unit separately. This segmentation allows the encoding-side device to perform simpler local processing rather than complex global compression, reducing processing complexity while maintaining image quality through geometric feature preservation.
Solution Approach 2:
The patent uses geometric shape recognition to create a simplified representation (copy) of the image content. Instead of performing complex compression processing, the system extracts geometric features and transmits indication information about these shapes, which can then be reconstructed at the decoding side, thereby reducing encoding complexity while preserving essential image information.
2Productivity
If image compression is performed to adapt to bandwidth constraints, then transmission efficiency is improved, but processing complexity increases
Solution Approach 1:
The patent extracts geometric features from image units and transmits only the indication information of these extracted features rather than the full compressed image data. This extraction approach reduces the amount of data to be transmitted (improving transmission efficiency) while avoiding complex compression algorithms at the encoding side.
Solution Approach 2:
The patent transforms image data from pixel-based representation to geometric parameter-based representation. By changing the representation parameters from continuous pixel values to discrete geometric shape descriptors, the system achieves more efficient transmission with reduced processing complexity at the encoding端.
Data Source
AI summary
An image processing method and apparatus to reduce storage resource consumption includes determining, by a server, a first geometric shape according to a first image unit in a first image from an encoding-side device, where a similarity between the first image unit and the first geometric shape falls within a preset range; and sending encoding information of the first image to a decoding-side device, where the encoding information of the first image includes indication information of the first geometric shape and indication information of a location of the first image unit in the first image.