Rasterized Data Processing via 2D Block Translation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video compression/decompression algorithms face inefficiencies in processing and storing image data, particularly due to the need for multiple memory transactions when handling rasterized lines of data, which can lead to slower data retrieval and processing compared to two-dimensional data blocks.
Innovation Solution
The proposed solution involves converting rasterized pixel data into two-dimensional data blocks, allowing for more efficient memory access and processing by organizing pixels into tiles that can be stored and retrieved in consecutive memory locations, enabling faster decompression and encoding through the use of translation and decompression logic, and mapping addresses to tile blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rasterized pixel data is processed using conventional methods, then the data can be stored in consecutive memory locations, but multiple memory transactions are required which reduces processing efficiency
Solution Approach 1:
The patent divides the image data into two-dimensional macro blocks (e.g., 16x16 pixels) that are stored in consecutive memory locations. This segmentation allows the data to be processed in manageable chunks while maintaining memory efficiency, resolving the contradiction between processing efficiency and memory access time by organizing data in a way that reduces the number of memory transactions needed.
Solution Approach 2:
The patent transitions from processing data in one-dimensional raster lines to two-dimensional macro blocks. This dimensional change allows for better memory coalescing and reduces the number of separate memory transactions required, thereby improving processing efficiency while reducing time loss from multiple memory accesses.
2Quantity of substance
If variable length decoding is used to encode images, then the amount of data can be reduced, but the precision of the image is reduced
Solution Approach 1:
The patent changes the parameter of data organization from raster lines to two-dimensional macro blocks, which affects how the data is processed during encoding and decoding. This parameter change enables more efficient processing that maintains image precision while still achieving data compression through techniques like motion compensation and predictive coding applied to the macro block structure.
3Productivity
If raster lines are converted to two-dimensional data blocks, then memory access efficiency is improved, but the complexity of the processing system increases
Solution Approach 1:
The patent introduces translation logic as an intermediary component that converts between raster line format and two-dimensional macro block format. This intermediary layer handles the format conversion and memory management, improving memory access speed while containing the complexity in a dedicated module rather than throughout the entire processing system.
Solution Approach 2:
The patent creates a mapping between raster line addresses and two-dimensional macro block addresses, effectively copying the address space relationships. This copying approach allows the system to maintain compatibility with existing raster-based processing while gaining the benefits of block-based memory access patterns, thereby improving speed without proportionally increasing complexity.
Data Source
AI summary
Devices, methods, and other embodiments associated with processing rasterized data are described. In one embodiment, an apparatus includes translation logic for converting lines of rasterized pixel data of a compressed image to a plurality of two-dimensional data blocks. The lines of rasterized pixel data are stored in consecutive memory locations. Each data block is stored in a consecutive memory location. The apparatus includes decompression logic for at least partially decompressing the compressed image based, at least in part, on the two-dimensional data blocks.