Frame Buffer Compressor With CRC Error Detection
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Solution Overview
Problem
Conventional image processing devices face limitations in processing capability due to increased bandwidth requirements for high-definition and high-frame rate videos, leading to reduced video recording and playback rates, necessitating effective data compression methods.
Innovation Solution
An image processing device equipped with a frame buffer compressor that compresses and decompresses data using a combination of prediction, entropy encoding, and cyclic redundancy check (CRC) modules, operating in both lossy and lossless modes to optimize data transfer and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data compression is implemented to reduce data size, then memory bandwidth requirements are reduced and processing speed increases, but data error detection capability deteriorates
Solution Approach 1:
The CRC calculation is performed in advance during the compression process, and the calculated CRC value is stored alongside the compressed data. This preliminary error detection mechanism ensures that data integrity can be verified without adding significant processing delay, as the CRC is pre-computed and attached to the data stream.
Solution Approach 2:
The CRC module acts as an intermediary between the compression process and data storage. It calculates a checksum based on the compressed data and attaches this verification information to the data stream, enabling error detection without requiring the entire data to be re-processed or stored in an uncompressed format.
2Manufacturing precision
If compression mode is set to lossless to maintain data accuracy, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The system allows dynamic switching between lossless and lossy compression modes based on configurable parameters. The compression algorithm adjusts its behavior according to these parameters, enabling lossless mode when data accuracy is critical and lossy mode when storage efficiency is prioritized, thus managing complexity through parameter-based mode selection rather than implementing all possible compression variants simultaneously.
3Reliability
If CRC verification is added to ensure data integrity, then reliability is improved, but processing time increases
Solution Approach 1:
The CRC calculation is performed in advance during compression, and the CRC value is stored with the compressed data. During decompression, only the lightweight verification step is needed, avoiding the time-consuming re-computation of CRC values. This preliminary action shifts the computational burden to the compression phase rather than the verification phase.
Solution Approach 2:
The CRC verification is integrated continuously into the data compression and decompression pipeline rather than being a separate batch process. As data flows through the system, CRC calculations and verifications occur continuously without interruption to the main data processing stream, minimizing overall processing time while maintaining integrity checks.
Data Source
AI summary
An image processing device includes a frame buffer compressor, which is configured to: (i) compress source data into compressed data having CRC bits appended thereto, and (ii) decompress the compressed data into output data and use the CRC bits to check for errors in the output data. A multimedia device is provided, which is configured to generate the source data in response to raw data. A memory device is provided, which is configured to store the compressed data. The frame buffer compressor may include an encoder configured to compress the source data into the compressed data with the CRC bits appended thereto, and a decoder configured to decompress the compressed data into the output data. The encoder may include a prediction module, which is configured to generate prediction data including reference data and residual data, from the source data.