Pixel Stream Video Compression for Lower Storage and Bandwidth
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Solution Overview
Problem
Current data compression techniques for sampled data, such as aperture sampling, do not provide sufficient compression for the increasing amounts of media content generated by electronic devices, leading to excessive storage space consumption and increased bandwidth and transmission time requirements.
Innovation Solution
The method involves compressing video data by extracting pixel data streams from each pixel in a video sensor and applying data compression to each stream individually, rather than compressing entire frames, using algorithms that discard data points based on allowable change thresholds or beam narrowing techniques to achieve lossless or lossy compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional frame-based video compression is used, then the compression process is simpler, but the compression ratio is insufficient and storage space consumption is excessive
Solution Approach 1:
The patent divides video data into individual pixel data streams, processing each pixel's temporal sequence separately rather than compressing entire frames together. This segmentation enables more granular compression control and achieves higher compression ratios by exploiting temporal redundancy within each pixel's time series while maintaining manageable processing complexity through systematic organization of the segmentation process
Solution Approach 2:
The patent transforms the traditional two-dimensional frame-based compression approach into a three-dimensional processing model by adding the temporal dimension. Instead of compressing spatial data (frames), the system compresses temporal data (sequences of pixel values over time), fundamentally changing the compression dimension and achieving superior compression efficiency
2Quantity of substance
If aperture sampling compression is applied, then some data reduction is achieved, but the compression ratio is still insufficient for modern media content volumes
Solution Approach 1:
The patent changes the fundamental parameter being compressed from spatial sampling (aperture sampling) to temporal sampling. By compressing the time series of pixel values and using threshold-based reconstruction, the system achieves higher compression ratios while maintaining signal fidelity through intelligent retention of significant temporal changes
3Loss of time
If pixel-level compression is implemented, then storage space and transmission time are reduced, but the processing complexity increases
Solution Approach 1:
The patent performs preliminary organization of video data into pixel-specific temporal sequences before compression. By pre-structuring the data in a format optimized for temporal compression algorithms, the system reduces the computational complexity of the actual compression process while achieving high compression ratios and reduced transmission time
Data Source
AI summary
A computer-implemented method for compressing video data comprises receiving a sequence of video data values, each video data value being a digital value from a successive one of a plurality of pixels that form a video sensor, the sequence of video data values resulting from successive frames of video captured by the video sensor; extracting the video data values for each pixel in turn to create a plurality of pixel data streams, each pixel data stream including the video data value for each frame of captured video for the pixel; and applying data compression to each pixel data stream to create compressed data for each pixel data stream.