Bit-Plane Data Array Encoding for Fixed-Rate Compression
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Solution Overview
Problem
Existing data compression methods for image and texture data in graphics processing systems are inefficient, leading to high storage and bandwidth demands, particularly in resource-constrained devices like digital cameras, and do not guarantee a fixed compression rate.
Innovation Solution
A method and apparatus for encoding data arrays using a frequency transform operation followed by bit plane coding, subdividing bit planes into sections, and encoding them recursively to achieve a fixed size data packet, ensuring efficient lossy compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional data compression methods are used for image and texture data, then storage and bandwidth demands are reduced, but compression efficiency is insufficient and throughput is limited
Solution Approach 1:
The patent segments the data compression process into distinct functional units: frequency transform module, bit plane decomposition module, and entropy encoding module. Each module processes specific aspects of the data independently, enabling parallel processing and improving overall throughput while maintaining efficient compression ratios for image and texture data
Solution Approach 2:
The patent transforms the compression approach by converting spatial domain data into frequency domain through transform operations, then decomposes into multiple bit planes. This dimensional transformation enables more effective exploitation of data redundancy and achieves higher compression efficiency with improved throughput compared to conventional single-domain methods
2Adaptability or versatility
If compression methods are applied to reduce storage demands, then bandwidth requirements decrease, but the compression rate is not fixed and resource-constrained devices still face limitations
Solution Approach 1:
The patent implements dynamic control mechanisms that allow the compression system to adapt to different operational requirements. The encoder can adjust processing parameters and select different encoding strategies based on available resources and desired compression rates, enabling fixed compression rate operation while optimizing energy consumption for resource-constrained devices
Solution Approach 2:
The patent employs parameter change techniques by modifying encoding parameters such as bit plane processing depth, transform block sizes, and entropy encoding precision. These parameter adjustments enable the system to achieve fixed compression rates while adapting to the processing capabilities and energy constraints of different devices, particularly mobile and embedded systems
Data Source
AI summary
Disclosed herein is a method of encoding an array of data elements comprising transforming the array from the spatial to the frequency domain, representing the frequency domain coefficients as a plurality of bit plane arrays, and encoding the set of frequency domain coefficients as a data packet having a fixed size by encoding the bit plane arrays in a bit plane sequence working from the bit plane array representing the most significant bit downwards until the data packet is full. Each bit plane array is encoded by recursively subdividing the bit plane array into respective sections and subsections down to the individual coefficients and including in the data packet, so long as there is available space, data indicating the locations of any (sub)sections in that bit plane array that for the first time in the bit plane sequence contain one or more coefficient(s) having a non-zero bit value.