Video Data Pruning via Example-Based Super-Resolution Patch Clustering
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Solution Overview
Problem
Existing video compression techniques using data pruning face issues such as information loss, artificial motion artifacts, and reduced coding efficiency due to the need for additional metadata transmission, particularly in approaches involving line or block removal and image epitome methods.
Innovation Solution
The method employs example-based super-resolution for data pruning, where patches from video frames are extracted, clustered, and packed into patch frames, with representative patches transmitted to the decoder, allowing for uniform downsizing of video frames and recovery of high-resolution information without additional metadata, thus preserving spatial and temporal smoothness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If line removal is used for data pruning, then video coding efficiency is improved, but information loss occurs leading to aliasing artifacts
Solution Approach 1:
The image is divided into multiple overlapping patches (e.g., 8x8 or 16x16 pixel blocks) that are systematically sampled at regular intervals. This segmentation allows the pruning process to work on localized regions while maintaining global image quality through the overlapping structure, preventing information loss that would occur with global line removal.
Solution Approach 2:
Patches are pre-processed and clustered before the actual pruning operation. By analyzing and grouping similar patches in advance, the system identifies which patches can be safely removed or downsampled without losing critical information. This preliminary analysis prevents aliasing artifacts by ensuring that only redundant patches are pruned.
2Adaptability or versatility
If block or region removal is used for data pruning, then flexibility for data pruning is improved, but information loss and aliasing artifacts still occur
Solution Approach 1:
The image is divided into multiple overlapping patches (e.g., 8x8 or 16x16 pixel blocks) that are systematically sampled at regular intervals. This segmentation allows the pruning process to work on localized regions while maintaining global image quality through the overlapping structure, preventing information loss that would occur with global line removal.
Solution Approach 2:
The patch sampling rate and patch size are adjustable parameters that can be modified based on the specific application requirements and image content characteristics. This allows flexible control over the degree of pruning while maintaining image quality, as the parameters can be optimized for different scenarios without causing information loss.
3Quantity of substance
If image epitome is used for data pruning, then compression is achieved, but encoding efficiency is reduced due to side information transmission
Solution Approach 1:
The invention extracts only the essential visual information from patches by downsampling them to a reduced resolution representation. Unlike image epitome that requires transmitting complex mapping relationships, this approach extracts only the core visual content at lower resolution, eliminating the need for side information transmission while maintaining compression efficiency.
Solution Approach 2:
Instead of transmitting complex epitome structures with surjective maps, the invention creates simplified copies of patch information at reduced resolution. These downsampled patch representations serve as sufficient proxies for the original high-resolution patches, enabling efficient compression without requiring additional metadata for reconstruction.
4Measurement precision
If line positions are optimized to minimize recovery error, then recovery accuracy is improved, but false removal of lines containing important information occurs
Solution Approach 1:
The image is divided into multiple overlapping patches (e.g., 8x8 or 16x16 pixel blocks) that are systematically sampled at regular intervals. This segmentation allows the pruning process to work on localized regions while maintaining global image quality through the overlapping structure, preventing information loss that would occur with global line removal.
Solution Approach 2:
Patches are pre-processed and clustered before the actual pruning operation. By analyzing and grouping similar patches in advance, the system identifies which patches can be safely removed or downsampled without losing critical information. This preliminary analysis prevents aliasing artifacts by ensuring that only redundant patches are pruned.
Data Source
AI summary
Methods and apparatuses for data pruning for video compression using example-based super resolution are provided. A method and apparatus for encoding is provided in which patches of video are extracted from input video, grouped together using a clustering method, and representative patches are packed into patch frames. The original video is downsized and sent either along with, or in addition to, the patch frames. At a decoder, the method and apparatus provided extract patches from the patch frames and create a patch library. The regular video frames are upsized and the low resolution patches are replaced by patches from the patch library by searching the library using the patches in the decoded regular frames as keywords. If there are no appropriate patches, no replacement is made. A post processing procedure is used to enhance the spatiotemporal smoothness of the recovered video.