Multi-Level Picture Data Compression for Embedded Systems
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Solution Overview
Problem
Existing picture data compression methods for embedded systems with limited resources either consume excessive RAM during decoding or result in data loss, making them unsuitable for tiny embedded systems with limited memory and display quality.
Innovation Solution
A multi-level compression method for picture data that involves obtaining original data, performing modulo operations, determining bit lengths for index data, constructing and compressing color and index tables, and applying secondary compression on the index tables to minimize data loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If existing compression algorithms are used for picture data, then compression ratio is improved, but data loss occurs and display quality deteriorates
Solution Approach 1:
The patent segments the picture data compression process into multiple stages: original data extraction through modulo operation, color table construction, index table generation, and multi-level compression. This segmentation allows each stage to be optimized independently, achieving lossless compression while maintaining high compression ratios.
Solution Approach 2:
The patent performs preliminary actions by constructing color tables and index tables before actual compression. The modulo operation is performed in advance to extract original data, and the color table is built beforehand to facilitate efficient compression. These preliminary actions enable the compression process to achieve both high compression ratios and lossless reconstruction.
2Productivity
If existing compression algorithms are used for picture data, then compression efficiency is improved, but RAM consumption increases
Solution Approach 1:
The patent changes key parameters by using modulo operation to extract original data, constructing compact color tables with optimized bit lengths, and generating index tables that reference the color table. These parameter changes enable efficient compression with minimal RAM consumption, as the compressed data structure uses fewer resources during both compression and decompression operations.
3Manufacturing precision
If picture data is stored in raw form, then picture quality is maintained, but flash memory space consumption increases
Solution Approach 1:
The patent creates a simplified copy of the picture data through color tables and index tables. Instead of storing the complete original picture data, it stores a color table containing unique color values and an index table containing references to these colors. This copying approach maintains picture quality while significantly reducing flash memory space consumption.
Solution Approach 2:
The patent uses a composite data structure combining color tables and index tables to represent picture data. This composite structure allows the system to store picture data in a compressed format that maintains quality while reducing storage requirements, effectively creating a new material for picture data representation.
Data Source
AI summary
A multi-level compression method for picture data includes: obtaining original data by performing modulo operation on a picture to-be-compressed; obtaining a first storage amount and a second storage amount by respectively storing the original data in a first container and a second container and calculating a size of data in the first container and a size of data in the second container; determining a bit length of index data, and constructing a color table and an initial index table; obtaining a target color table by identifying a minimum value in the color table and subtracting the minimum value from each data in the color table; obtaining a first compressed index table by compressing the initial index table according to the bit length; and obtaining a second compressed index table by identifying a locator in the first compressed index table and compressing the first compressed index table according to the locator.