Hybrid NAL Unit Types for High-Resolution Image Decoding
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Solution Overview
Problem
There is a need for high-efficient image compression technology to effectively transmit, store, and reproduce high-resolution and high-quality images, as existing technologies face challenges with increased transmission and storage costs due to the higher amount of information required for these images.
Innovation Solution
An image encoding/decoding method and apparatus that utilizes a mixed NAL unit type and a subpicture merging operation, allowing for improved encoding/decoding efficiency by determining and utilizing different NAL unit types for slices within a picture, including a RASL_NUT for random access decodable leading pictures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image data is transmitted and stored using existing compression technology, then image quality and resolution are improved, but transmission cost and storage cost increase due to the larger amount of information
Solution Approach 1:
The image data is divided into multiple slices, and each slice is assigned a specific NAL unit type (RASL_NUT or RADL_NUT). This segmentation allows different parts of the image to be processed and transmitted with different priority levels, reducing the overall amount of data that needs to be transmitted while maintaining high image quality through selective decoding of critical slices.
Solution Approach 2:
Different NAL unit types are assigned to different slices based on their importance and decoding requirements. RASL_NUT slices are designed for random access decodable leading pictures while RADL_NUT slices are for other decodable pictures. This local differentiation optimizes transmission efficiency by allowing the receiver to selectively decode only the necessary slices based on current needs, reducing unnecessary data transmission.
2Productivity
If traditional NAL unit types are used for all slices in a picture, then encoding simplicity is maintained, but encoding/decoding efficiency is reduced
Solution Approach 1:
The NAL unit type for each slice is dynamically determined based on the picture type and slice characteristics rather than using a static uniform type for all slices. The decoding apparatus determines the NAL unit type of each slice based on the picture type and slice characteristics, allowing the system to adapt to different decoding scenarios and optimize efficiency for each specific case.
Solution Approach 2:
The patent introduces new NAL unit type parameters (RASL_NUT and RADL_NUT) and changes the parameter structure of slice headers to include NAL unit type information. This parameter change enables more flexible and efficient encoding/decoding by allowing different NAL unit types to be assigned to different slices based on their specific requirements, thereby improving overall processing efficiency.
Data Source
AI summary
An image encoding/decoding method and apparatus are provided. The image decoding method includes obtaining, from a bitstream, network abstraction layer (NAL) unit type information of at least one NAL unit including coded image data, determining at least one NAL unit type of one or more slices in the current picture based on the obtained NAL unit type information, and decoding the current picture based on the determined NAL unit type. The current picture is determined to be a random access skipped leading (RASL) picture, based on the determined NAL unit type including a RASL picture NAL unit type (RASL_NUT). When an intra random access point (IRAP) picture associated with the RASL picture is a first picture in decoding order, the RASL picture is decoded, based on the RASL picture including one or more slices having a random access decodable leading (RADL) picture NAL unit type (RADL_NUT).