Image Coding Device Zone Segmentation Spatial Correlation
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Solution Overview
Problem
Current video coders and decoders do not achieve satisfactory coding/decoding performance due to a lack of adaptability in handling different image formats and spatial correlations, leading to inefficient bitrate usage and increased complexity.
Innovation Solution
A method and device that split images into distinct zones, allowing for adaptive coding and decoding using two different schemes within the same encoder/decoder, where one zone's coding parameters are copied for the second zone, optimizing coding performance by exploiting spatial correlations and reducing bitrate complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a single coding scheme is used for all blocks in the image, then the device complexity is reduced, but the coding performance is insufficient for different image formats and spatial correlations
Solution Approach 1:
The image is divided into multiple zones (first zone and second zone) with different coding schemes applied to each zone. This segmentation allows the encoder to handle different spatial correlations and image formats appropriately in different regions, improving overall coding performance while managing device complexity through structured division.
Solution Approach 2:
Different coding schemes are applied to different zones of the image based on their specific characteristics. The first coding scheme is used for the first zone and the second coding scheme for the second zone, allowing each region to be coded with the most appropriate method for its spatial correlation properties, thereby optimizing local coding quality.
2Productivity
If adaptive coding with multiple schemes is implemented, then coding efficiency is improved, but the complexity of the encoder increases
Solution Approach 1:
The encoder is structured to process different zones with different coding schemes, improving coding efficiency by adapting to local characteristics. The segmentation into first and second zones allows efficient handling of different spatial correlations while maintaining manageable encoder complexity through organized processing stages.
Solution Approach 2:
The encoder copies coding parameters from previously coded blocks in the first zone when coding blocks in the second zone. This copying mechanism reduces the bitrate required for the second zone while maintaining coding efficiency, as many parameters can be reused without re-encoding, thus improving productivity without proportionally increasing encoder complexity.
3Quantity of substance
If coding parameters are copied from the first zone for the second zone, then the bitrate is reduced, but the adaptability to different image formats decreases
Solution Approach 1:
The encoder applies different coding strategies to different zones: the first zone uses standard coding with full parameter encoding, while the second zone uses parameter copying from the first zone. This local differentiation reduces overall bitrate by exploiting spatial correlations between zones, while maintaining adaptability through the ability to handle different image formats in each zone independently.
Solution Approach 2:
The coding device is designed to handle multiple image formats (2D video sequences, 3D images, 360° videos) using the same zonal coding structure. The first and second zones can be configured differently depending on the input format, making the system universal and adaptable while still benefiting from parameter copying to reduce bitrate.
4Manufacturing precision
If the image is divided into zones with different coding schemes, then spatial correlations are exploited better, but the device complexity increases
Solution Approach 1:
The image is segmented into first and second zones with distinct coding schemes, allowing better exploitation of spatial correlations within each zone. This segmentation improves coding precision by matching the coding approach to the local characteristics of each region while keeping device complexity manageable through structured organization.
Solution Approach 2:
Coding parameters are copied from blocks in the first zone to corresponding blocks in the second zone, exploiting the spatial correlations between these zones. This copying approach improves coding precision by utilizing redundant information across zones while reducing device complexity compared to fully independent coding of each zone.
Data Source
AI summary
A method and device for encoding an image divided into blocks. The image contains separate first and second zones). The encoding implements the following, for at least one current block of the image: determining to which of the first and second zones the current block pertains; if the current block pertains to the first zone, encoding the current block by using a first encoding method; if the current block pertains to the second zone, encoding the current block by using a second encoding method including the following: from the position of the current block in the second zone, identifying a previously encoded, then decoded block located in the first zone of the image; and reproducing the value of at least one encoding parameter associated with the identified block.