Video Data Processing Using Image Signatures for Static Region Compression
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Solution Overview
Problem
Processing video data is computationally intensive, leading to energy consumption and heat generation, particularly in battery-powered devices, and existing video compression methods are also energy-intensive, burdening processing resources.
Innovation Solution
A method that classifies regions of video frames as changing or static using an image signature algorithm, generating a compressed output video stream with a higher data reduction rate for static regions, thereby reducing the amount of data processed and transferred, and requiring fewer processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If video data is processed using conventional compression methods, then data reduction is achieved, but energy consumption and processing resource requirements increase
Solution Approach 1:
The video frame is divided into multiple regions (e.g., first region, second region, third region) that are processed differently. Static regions are compressed at a higher rate while changing regions are compressed at a lower rate or not compressed at all. This segmentation allows the system to reduce data size for static portions without unnecessarily processing dynamic portions, thereby reducing overall energy consumption compared to uniform compression methods.
Solution Approach 2:
Different compression quality levels are applied to different regions of the video frame based on their characteristics. Static regions receive higher compression (lower quality retention) while changing regions receive lower compression (higher quality retention). This local differentiation optimizes the balance between data reduction and information preservation, reducing total data volume without significantly impacting perceived video quality, thus lowering energy consumption.
2Quantity of substance
If video data is processed using conventional compression methods, then data reduction is achieved, but processing resources and computational intensity increase
Solution Approach 1:
The processing system divides the video frame into regions and applies different processing strategies to each. By segmenting the processing task, the system avoids the computational burden of applying high-compression algorithms to entire frames, especially those with significant changes. This reduces the total processing resources required while achieving substantial data reduction through targeted compression of static regions.
Solution Approach 2:
Instead of applying full compression to all regions, the system applies compression selectively only where needed (in static regions). This partial action approach reduces computational complexity by avoiding unnecessary processing in dynamic regions, while still achieving significant data reduction through the compression of static portions that occupy substantial portions of the frame.
3Reliability
If all video frames are processed at full resolution, then video quality is maintained, but energy consumption and data transfer requirements increase
Solution Approach 1:
The system maintains different quality levels for different regions. Changing regions maintain higher quality (less compression) to preserve important dynamic information, while static regions use lower quality (higher compression) to reduce data transfer requirements. This local quality differentiation ensures that energy is not wasted on compressing regions that would lose important information, while still achieving overall data reduction and energy savings.
Data Source
AI summary
A method for processing video data, comprising: receiving a stream of input video data representative of a number of successive frames generated by an imaging device's image sensor; selecting at least some of the frames; for each selected frame: determining, using an image signature algorithm, a signature for each region of the given selected frame; and, based on such signatures, classifying each region in that frame as either a changing or a static region; and generating an output video data stream that is a compressed version of the input video data, with a greater average data reduction rate for static region data than for changing region data, of the selected frames. The signature algorithm is such that a region's signature has substantially smaller size than the input data representative of that region, and such that signatures for visually similar regions are the same or similar.