Video Data Interpolation Using Embedded Content Metadata
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for reconstructing downscaled or compromised video data are limited in performance and complexity, as they lack information about the original nature and characteristics of the content.
Innovation Solution
The method involves signaling to a device the appropriate conversion technique for reconstructing downscaled or compromised video data back to its original or higher resolution, using algorithms such as separable or non-separable filters and edge adaptive interpolation, while analyzing and characterizing the signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If current reconstruction methods are used for downscaled video data, then device complexity is reduced, but conversion performance and image quality deteriorate due to lack of information about original content characteristics
Solution Approach 1:
The encoder performs preliminary analysis of the original video content characteristics before downsampling and embeds this information into the bitstream. This allows the decoder to receive pre-characterized data about the original content, enabling more accurate reconstruction without requiring complex real-time analysis at the decoding stage.
Solution Approach 2:
Metadata acts as an intermediary carrier that conveys information about original content characteristics from the encoder to the decoder. This metadata includes statistical properties and structural information that bridge the information gap created by downsampling, allowing the decoder to make informed reconstruction decisions without directly accessing the original high-resolution content.
2Productivity
If downsampling is applied to reduce bandwidth, then transmission efficiency is improved, but resolution and detail information are lost
Solution Approach 1:
The system changes the parameter representation by encoding statistical characteristics and structural metadata alongside the downsampled video data. These additional parameters capture essential information about the original content's resolution, texture, and structural properties, allowing the decoder to reconstruct details that would otherwise be lost in the downsampling process.
Solution Approach 2:
The encoded bitstream becomes a composite structure combining downsampled video data with embedded metadata about original content characteristics. This composite representation preserves both the compressed visual information and the analytical information needed for accurate reconstruction, effectively combining the benefits of compression with the preservation of original content properties.
3Speed
If simple reconstruction algorithms are used, then processing speed is improved, but image quality and conversion accuracy deteriorate
Solution Approach 1:
Complex analysis and characterization of content properties is performed in advance during encoding, with results embedded as metadata. During decoding, the system uses these pre-computed characteristics to guide simple, efficient reconstruction algorithms, achieving high conversion accuracy without requiring complex real-time processing.
Solution Approach 2:
The encoded bitstream contains self-descriptive metadata that enables the decoder to automatically adapt its reconstruction process to the specific characteristics of the content. The data essentially describes itself, allowing the decoding system to optimize its processing approach without external intervention or complex analysis.
Data Source
AI summary
An encoding device evaluates a plurality of processing and/or post-processing algorithms and/or methods to be applied to a video stream, and signals a selected method, algorithm, class or category of methods/algorithms either in an encoded bitstream or as side information related to the encoded bitstream. A decoding device or post-processor utilizes the signaled algorithm or selects an algorithm/method based on the signaled method or algorithm. The selection is based, for example, on availability of the algorithm/method at the decoder/post-processor and/or cost of implementation. The video stream may comprise, for example, downsampled multiplexed stereoscopic images and the selected algorithm may include any of upconversion and/or error correction techniques that contribute to a restoration of the downsampled images.