Image Quality Parameter Clustering for Adaptive Transmission Processing
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Solution Overview
Problem
Existing image processing technologies struggle to dynamically improve image quality based on transmission characteristics and image features, and they lack the ability to update parameters effectively for continuous quality enhancement.
Innovation Solution
An image processing apparatus that determines image quality parameters using neural networks trained to analyze transmission characteristics and image features, performs image quality processing, and updates these parameters based on user viewing history through interworking with an external server to optimize image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image data is transmitted and processed remotely, then data security and privacy are improved, but transmission time and power consumption increase
Solution Approach 1:
The patent segments image processing into two parts: sensitive operations (encryption key generation, authentication) are performed locally on the terminal device, while non-sensitive processing (image enhancement, filtering) is transmitted to the server. This segmentation allows security-critical functions to remain private while still benefiting from remote processing capabilities.
Solution Approach 2:
The terminal device performs preliminary processing of image data before transmission, including extracting only necessary features and pre-encrypting sensitive information. This preliminary action reduces the amount of data that needs to be transmitted and ensures security is established before data leaves the local device.
2Reliability
If image data is transmitted and processed remotely, then data security and privacy are improved, but power consumption increases
Solution Approach 1:
The patent segments image processing into two parts: sensitive operations (encryption key generation, authentication) are performed locally on the terminal device, while non-sensitive processing (image enhancement, filtering) is transmitted to the server. This segmentation allows security-critical functions to remain private while still benefiting from remote processing capabilities.
Solution Approach 2:
The terminal device performs preliminary processing of image data before transmission, including extracting only necessary features and pre-encrypting sensitive information. This preliminary action reduces the amount of data that needs to be transmitted and ensures security is established before data leaves the local device.
3Speed
If all image processing is performed locally, then processing speed is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent segments image processing into two parts: sensitive operations (encryption key generation, authentication) are performed locally on the terminal device, while non-sensitive processing (image enhancement, filtering) is transmitted to the server. This segmentation allows security-critical functions to remain private while still benefiting from remote processing capabilities.
Solution Approach 2:
The server provides universal image processing capabilities that can be accessed by multiple terminal devices. Instead of each device having full processing capabilities, the server handles common processing tasks (enhancement, filtering, compression) that can benefit from centralized resources, reducing individual device complexity.
4Device complexity
If image processing is outsourced to server, then device complexity is reduced, but transmission bandwidth requirements increase
Solution Approach 1:
The terminal device performs preliminary processing of image data before transmission, including extracting only necessary features and pre-encrypting sensitive information. This preliminary action reduces the amount of data that needs to be transmitted to the server, thereby reducing bandwidth requirements.
Solution Approach 2:
The patent extracts and processes only the essential features of image data locally before transmission. By taking out and handling critical processing tasks (feature extraction, encryption) at the source, the system reduces the volume of data that needs to be transmitted over the network.
Data Source
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AI summary
An image processing apparatus includes: a memory storing one or more instructions; and a processor by executing the one or more instructions stored in the memory is configured to: extract a first image feature from a first image; search for, based on a transmission characteristic of the first image and the first image feature, a first cluster corresponding to the first image from among a plurality of clusters stored in the image processing apparatus, each cluster including a representative image feature and a representative image quality parameter; perform image quality processing on the first image based on a first representative image quality parameter in the first cluster; obtain, based on the first image that has undergone the image quality processing, a first update parameter obtained by updating the first representative image quality parameter; and update the plurality of clusters based on the first update parameter.