Recursive Block Image Decoding for 360-Degree Projection Compression
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Solution Overview
Problem
Existing image processing systems struggle with the massive data generated for 360-degree images in virtual and augmented reality, necessitating improved performance in image encoding and decoding, particularly for 360-degree images.
Innovation Solution
A method for decoding 360-degree images involves generating a predicted image using syntax information, combining it with a residual image, and reconstructing the image in a specific projection format, utilizing techniques like Equi-Rectangular Projection, CubeMap Projection, and IcoSahedral Projection to enhance compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image encoding/decoding methods are used for 360-degree images, then the processing can be performed with existing systems, but the performance is insufficient for handling the massive data generated by multi-view images
Solution Approach 1:
The patent applies segmentation by dividing the 360-degree image processing into distinct stages: encoding stage (separating prediction and residual processing) and decoding stage (separate reconstruction steps). The decoding process is segmented into receiving bitstream, generating predicted image, acquiring residual image, and combining them to reconstruct the final image, enabling efficient handling of large data volumes through structured processing
2Productivity
If the image is reconstructed without considering projection format characteristics, then the decoding process is simpler, but the compression performance is reduced
Solution Approach 1:
The patent applies local quality by tailoring the decoding process to specific projection format characteristics. Different reconstruction methods are applied based on the projection type (e.g., equirectangular, cube map, fish-eye), where the decoding complexity and processing steps are adapted to the local requirements of each projection format, optimizing compression performance for each specific case
3Measurement precision
If image expansion is performed on the reference picture, then the prediction accuracy is improved, but the processing time and computational load increase
Solution Approach 1:
The patent applies preliminary action by performing image expansion on the reference picture before the prediction process. The reference picture is pre-processed with appropriate expansion (e.g., using expansion filters or interpolation) to match the resolution and characteristics of the current picture, ensuring that prediction operations work with optimally prepared data, thereby improving prediction accuracy while managing computational load through advance preparation
Data Source
AI summary
Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.