Compression Adaptive Module for Ultra High Definition Video Detail Restoration
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Solution Overview
Problem
Current electronic systems fail to effectively display high-quality three-dimensional images due to degraded image quality from standard definition or full high definition video on ultra high definition displays, caused by compression and lower resolution, resulting in blurry images with lost fine details and noise artifacts.
Innovation Solution
An electronic system with a compression adaptive module that restores lost details in video streams using frequency lifting based super-resolution technology, adapting to compression information to provide a high resolution output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard definition or full high definition video is displayed on ultra high definition displays, then the display can show three-dimensional images, but the image quality is degraded resulting in blurry images with lost fine details
Solution Approach 1:
The system performs preliminary processing of the video stream before display by extracting compression information and applying frequency lifting-based super-resolution enhancement. This preliminary action restores lost fine details and enhances image quality before the video is displayed on the ultra high definition display, preventing the degradation that would occur with direct display of compressed low-resolution video.
Solution Approach 2:
The system changes the resolution parameter of the video stream from standard definition or full high definition to ultra high definition by using frequency lifting-based super-resolution technology. This parameter change allows the system to maintain high image quality and fine details while displaying on ultra high definition displays, resolving the contradiction between display capability and image quality.
2Productivity
If compression is applied to video streams, then the video can be transmitted efficiently, but the image quality deteriorates with artifacts at block boundaries and propagation of accumulated noise
Solution Approach 1:
The system uses feedback from compression information extracted from the video stream to adaptively adjust the frequency lifting-based super-resolution enhancement process. By analyzing the compression characteristics and using this feedback, the system can restore image quality and reduce artifacts while maintaining the efficiency benefits of compression for video transmission.
Solution Approach 2:
The system converts the harmful effects of compression (block boundary artifacts, accumulated noise) into beneficial information by extracting compression characteristics from the video stream. This extracted information is then used to guide the super-resolution enhancement process, transforming the compression artifacts into a signal for improving image quality while maintaining transmission efficiency.
3Length of moving object
If regular image upscaling or interpolation is applied, then the resolution can be increased, but the image sharpness and fine detail are insufficient
Solution Approach 1:
The system replaces conventional mechanical upscaling or interpolation methods with frequency lifting-based super-resolution technology. This substitution enables the system to achieve higher resolution and improved image sharpness by working in the frequency domain to restore fine details that are lost during compression and standard upscaling processes.
Data Source
AI summary
An electronic system includes: a communication unit configured to provide a transport stream; a storage unit, coupled to the communication unit, configured to provide a stream from the transport stream; and a control unit, coupled to the storage unit, configured to restore details to the stream by a compression adaptive module for a high resolution output.