Guided Transcoding via Deflation Inflation for Storage Reduction
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Solution Overview
Problem
Current transcoding solutions for video on demand (VoD) services face challenges in balancing storage capacity and computational complexity, as they either require large storage or high computational overhead, failing to meet industry demands for reduced storage and low computational complexity simultaneously.
Innovation Solution
The proposed method employs a variant of guided transcoding, known as deflation/inflation, which uses categories derived from original estimated coefficients to efficiently code and decode delta transform coefficients, reducing storage capacity while maintaining low computational complexity through procedures like sign guessing, remapping, and context selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simulcast approach is used to store multiple bit rates and quality levels, then low server complexity is achieved, but large storage capacity is required
Solution Approach 1:
The patent extracts and removes the residual data and transform coefficients from the low quality bit streams, keeping only the side information (motion information, intra mode information, transform block information). This extraction reduces storage requirements while maintaining the ability to reconstruct low quality streams through guided transcoding.
Solution Approach 2:
The patent performs preliminary encoding to generate side information from high quality bit streams before actual playback requests. This pre-computed side information is stored instead of complete low quality streams, enabling faster and more storage-efficient transcoding when requests arrive.
2Quantity of substance
If transcoding approach is used to reduce storage demands, then storage capacity is reduced, but high computational complexity is incurred
Solution Approach 1:
The patent performs preliminary encoding to generate side information (motion information, intra mode information, transform block information) from high quality bit streams before actual playback requests. This pre-computed side information is stored instead of complete low quality streams, enabling faster and more storage-efficient transcoding when requests arrive.
Solution Approach 2:
The patent extracts and removes the residual data and transform coefficients from the low quality bit streams, keeping only the side information. This extraction reduces storage requirements while maintaining the ability to reconstruct low quality streams through guided transcoding.
3Device complexity
If guided transcoding is used to reduce both computational complexity and storage requirements, then both parameters are improved, but complex encoding procedures are required
Solution Approach 1:
The patent applies parameter changes by quantizing the side information at different quality levels and using delta encoding to represent differences between high quality and low quality parameters. This allows efficient storage and reconstruction of multiple quality versions while reducing both storage requirements and computational complexity.
Solution Approach 2:
The patent segments the video encoding into separate components: side information (motion vectors, mode information, transform block information) and residual data. By segmenting and selectively storing only the essential side information, the patent reduces storage requirements while maintaining the ability to perform guided transcoding efficiently.
Data Source
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AI summary
There are provided mechanisms of guided transcoding. The methods are performed by a decoder, for producing original transform coefficients, and by an encoder, for producing coded delta transform coefficients. A decoding method comprises deriving a predicted residual block. The decoding method comprises transforming the predicted residual block using a forward transform, thereby producing a plurality of original estimated coefficients, the plurality of OECs comprising a first OEC. The decoding method comprises quantizing the plurality of OECs, thereby producing a plurality of quantized estimated transform coefficients comprising a first ETC corresponding to the first OEC. The decoding method comprises selecting a category based on the first OEC. The decoding method comprises decoding a first coded delta transform coefficient (DTC) corresponding to the first OEC, thereby producing a first decoded DTC, wherein the decoding comprises using the selected category to decode the first coded DTC. The decoding method comprises computing a first original transform coefficient by adding the first decoded DTC to the first ETC.