Parallel Image Decoding Layout for High-Resolution Video
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Solution Overview
Problem
Conventional image data processing technologies face challenges in efficiently processing high-resolution videos due to hardware limitations, where the processing speed is restricted by the need to decompress front-end data before back-end data, leading to unstable video playback and inefficient storage allocation.
Innovation Solution
A method and system that re-arranges image pixels during encoding, allowing simultaneous decoding of multiple pixels by grouping them according to the number of decoding circuits, enabling synchronous decoding and reducing the dependency on fixed bitstream length, thus improving processing speed and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If front-end data is decompressed before back-end data in sequential order, then decoding accuracy is maintained, but processing speed is limited by hardware clock speed
Solution Approach 1:
The patent segments the image data into multiple independent groups (first group, second group, etc.), where each group can be decoded independently by separate decoding circuits. This segmentation allows parallel processing of multiple pixel groups simultaneously, breaking the sequential dependency constraint while maintaining decoding accuracy through proper group organization and independent decoding paths.
2Productivity
If storage space is increased to decode multiple pixels simultaneously, then processing speed improves, but resource allocation becomes inefficient due to unknown data length
Solution Approach 1:
The patent applies preliminary action by re-arranging and grouping pixels during the encoding phase according to a specific arrangement order. This pre-processing organizes the data structure so that when decoding occurs, multiple pixel groups can be processed simultaneously without requiring excessive storage space. The grouping is done in advance, allowing the decoding system to allocate storage efficiently based on known group sizes rather than unknown individual pixel lengths.
3Productivity
If pixels are grouped by numbering interval equal to the number of decoding circuits, then simultaneous decoding is enabled, but encoding complexity increases
Solution Approach 1:
The patent changes the parameter of pixel arrangement by applying a specific arrangement order that groups pixels with numbering intervals equal to the number of decoding circuits. This parameter change transforms the raw pixel sequence into organized groups that can be directly mapped to multiple decoding circuits. The transformation is systematic and rule-based, making the encoding process manageable despite the increased organizational requirements, while enabling efficient parallel decoding.
Data Source
AI summary
A method for processing image data and a system thereof are provided. The method is operated in the system including an encoding system and a decoding system. In the decoding system, multiple image data packages are received from the encoding system. The image data packages include multiple encoded data that are formed by encoding the pixels of an image and the pixels are beforehand rearranged according to an arrangement order. The arrangement order is exemplarily made based on the quantity of encoding circuits of the encoding system. In the decoding system, the encoded data received from the encoding system are sequentially stored in a memory according to the arrangement order. The decoding circuits start to decode the encoded data from an initial code synchronously for enhancing decoding performance. The method can be applied to decoding of high resolution images. The image is reproduced after the decoding process.