Panorama Video Resampling Nested Polygonal Chain Scan
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Solution Overview
Problem
Current video coding systems face challenges in efficiently encoding and decoding panoramic video content, particularly in handling 360-degree images, where existing methods often result in non-scalable and inefficient compression due to the discarding of information, leading to suboptimal bitrate and quality trade-offs.
Innovation Solution
The method involves resampling and rearranging sample rows of a panorama picture into resampled arrays along nested polygonal chains, allowing for more efficient encoding and decoding by adjusting sampling density and packing these arrays into video frames, which can be used for intra, inter, or inter-layer prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If conventional video coding methods are used for panoramic content, then encoding simplicity is maintained, but compression efficiency and quality deteriorate due to information discarding
Solution Approach 1:
The panorama picture is divided into multiple regions (top, middle, bottom) with different sampling densities. Each region is processed independently with appropriate sampling rates, allowing the system to retain important information while reducing overall data volume. This segmentation enables efficient compression without uniformly discarding information across the entire panorama.
Solution Approach 2:
Different sampling densities are applied to different regions of the panorama picture. The middle region maintains higher sampling density to preserve quality, while top and bottom regions use lower density. This local quality approach optimizes the balance between compression efficiency and visual quality in different areas.
2Loss of substance
If uniform sampling density is used across the panorama picture, then processing simplicity is maintained, but bitrate efficiency deteriorates
Solution Approach 1:
The patent applies different sampling densities to different spatial regions of the panorama picture. The middle region uses higher sampling density to preserve important visual information, while top and bottom regions use lower density. This local quality differentiation improves bitrate efficiency by allocating bits according to regional importance rather than uniformly across the entire image.
Solution Approach 2:
The sampling density parameter is changed across different regions of the panorama picture. By varying the sampling rate from region to region (higher in middle, lower in top/bottom), the system optimizes bitrate efficiency while adapting to the spatial characteristics of panoramic content.
3Manufacturing precision
If high sampling density is retained throughout the panorama, then quality is preserved, but compression efficiency deteriorates
Solution Approach 1:
The patent preserves high quality in the middle region by maintaining higher sampling density, while accepting lower quality in top and bottom regions where lower sampling density is applied. This local quality preservation strategy maintains manufacturing precision where it matters most while improving overall compression efficiency.
Solution Approach 2:
Instead of applying high sampling density uniformly across the entire panorama (excessive action), the patent applies high sampling density only to the middle region where it is most needed (partial action). This selective approach preserves quality where necessary while improving compression efficiency by reducing sampling in less critical areas.
Data Source
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AI summary
The invention relates to method and technical equipment for video coding. An encoding method comprises resampling a plurality of sample rows of a picture (600) into a plurality of resampled sample rows (601 -612); and rearranging the resampled sample rows along a nested polygonal chain scan into a rearranged sample array (650 and 670). A decoding method comprises obtaining a rearranged sample array comprising a plurality of resampled sample rows following a nested polygonal chain scan; extracting a resampled sample row by treating a polygonal chain of the nested polygonal chain scan as a onedimensional signal along a scan order; resampling the resampled sample row into a sample row; and arranging the sample row into a sample array.