Gray Code Image Coding for Fixed-Length Compression Access
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Solution Overview
Problem
Existing image coding methods face challenges in achieving fast data transfer and reducing memory usage while maintaining image quality, particularly due to processing delays and increased circuit complexity caused by variable length coding and quantization errors, especially in darker image areas.
Innovation Solution
An image coding method that converts pixel data to Gray code and quantizes bit change information using exclusive OR operations, allowing for fixed-length coding without depending on signal levels, thereby reducing processing delays and memory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If variable length coding is used for image compression, then compression ratio is improved, but processing delay increases and random accessibility is lost
Solution Approach 1:
The patent changes the parameter of code length from variable to fixed by using Gray code conversion. This allows the coding system to maintain a constant code length while still achieving compression through the properties of Gray code, thereby enabling random accessibility and reducing processing delay associated with variable length decoding.
Solution Approach 2:
The patent replaces the traditional mechanical decoding process of variable length codes with a substitution based on Gray code properties. Instead of requiring sequential decoding of variable length codes, the system uses Gray code conversion which allows for fixed length coding, eliminating the processing delay and enabling direct random access to coded data.
2Quantity of substance
If quantization width is increased to reduce data amount, then compression is improved, but quantization errors increase especially in darker areas
Solution Approach 1:
The patent changes the parameter of quantization from direct pixel value quantization to quantization of bit change information. By converting to Gray code and quantizing only the bit changes, the system achieves compression while maintaining precision, as the quantization errors do not propagate and affect darker areas less severely.
Solution Approach 2:
The patent introduces Gray code conversion as an intermediary step between the original pixel data and the quantization process. This intermediary transformation allows the system to quantize bit change information rather than absolute values, reducing quantization errors in darker areas while still achieving compression.
3Speed
If higher operating frequency and larger memory capacity are used, then data transfer capability is improved, but cost increases
Solution Approach 1:
The patent changes the parameter of code structure to fixed length using Gray code, which simplifies the data transfer requirements. This allows the system to achieve efficient data transfer without requiring higher operating frequencies or larger memory capacities, thereby reducing cost while maintaining performance.
4Speed
If fixed length coding is used to secure bus bandwidth, then data transfer efficiency is improved, but compression ratio decreases
Solution Approach 1:
The patent changes the parameter of what is being coded from absolute pixel values to bit change information. This allows fixed length coding to maintain both the bus bandwidth efficiency and achieve compression, as the bit change information requires fewer bits to represent while still capturing the essential image data.
Data Source
AI summary
An image coding method includes: a predictive pixel generation step of generating a predictive value from at least one surrounding pixel located near a compression target pixel; a code conversion step of code-converting the pixel data to generate a Gray code; and quantizing bit change information (exclusive OR) between the generated Gray code and a Gray code of the predictive value to a quantization value, to compress the pixel data. This prevents significant image quality degradation, so that high image quality can be achieved.