Video Up-scaling Using Fractal Zooming and Wavelet Transforms
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Solution Overview
Problem
Current video up-scaling technologies are inefficient and costly, often replicating existing resolution lines to create the illusion of higher quality without actual improvement, failing to effectively convert standard definition (SD) video to high definition (HD) quality, particularly for legacy content.
Innovation Solution
The use of fractal geometry to represent complex images in a compact mathematical form, allowing for infinite scaling without quality loss, combined with techniques like de-correlating color transforms, artifact filtering, and simultaneous calculation of transformation values, enables efficient and cost-effective conversion of SD video to HD quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If current hardware up-scaling solutions are used, then video resolution can be increased, but processing speed becomes very slow and implementation cost becomes very expensive
Solution Approach 1:
The patent transforms the video up-scaling problem from a spatial domain operation to a frequency domain operation using wavelet transforms. By changing the domain parameter from spatial pixels to frequency coefficients, the system achieves both high resolution output and fast processing through parallel computation of frequency components, resolving the contradiction between quality and speed.
Solution Approach 2:
The patent replaces traditional mechanical interpolation methods (which replicate pixels and scan lines) with a mathematical transformation system based on wavelet theory. This substitution enables the system to generate high-resolution content through computational frequency analysis rather than simple geometric replication, achieving both quality improvement and processing efficiency.
2Manufacturing precision
If current hardware up-scaling solutions are used, then video resolution can be increased, but implementation cost becomes very expensive
Solution Approach 1:
The patent replaces complex hardware interpolation circuits with a software-based wavelet transformation algorithm. By substituting physical mechanical systems with mathematical computations, the implementation cost is dramatically reduced while maintaining high resolution quality, making the technology accessible for consumer applications.
Solution Approach 2:
The wavelet-based up-scaling system is designed to be universally applicable across different video formats, resolutions, and content types. This multi-functionality reduces the need for specialized hardware for each application, thereby lowering overall implementation costs while delivering consistent high-quality results across diverse use cases.
3Area of stationary object
If traditional up-scaling methods are used, then video can be displayed at higher resolution, but the quality of actual resolution is not improved, only the illusion of fuller picture is created
Solution Approach 1:
The patent replaces pixel replication methods with wavelet-based frequency domain synthesis. Instead of simply duplicating existing pixels to fill space, the system computes new high-resolution frequency components and transforms them back to spatial domain, creating genuine resolution improvement rather than visual illusion.
Solution Approach 2:
The patent transitions the up-scaling operation from two-dimensional spatial pixel manipulation to three-dimensional frequency-space transformation. By adding the frequency domain dimension to the processing, the system can synthesize new image information that genuinely improves resolution quality rather than merely expanding display area through replication.
Data Source
AI summary
Methods, systems, devices, and implementing technologies for up-scaling an original source video from a lower, first resolution to a desired output video having a higher, second resolution, using fractal zooming techniques to replace individual source pixels in each respective image frame of the original source video with a plurality of proposed replacement pixels in the vertical and horizontal dimensions having similar characteristics as the individual source pixel, reducing noise associated with each respective frame of the desired output video, re-sizing, as necessary, each respective replacement frame to the second resolution, and outputting each zoomed replacement frame to generate the desired output video, which is an up-scaled version of the original source video. The quality of the up-scaled output video is improved by using artifact filtering and linear smoothing techniques after the initial search and replace steps of the fractal zooming process.