Lossless Pixel Compression via Embedded Format Detection
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Solution Overview
Problem
Current lossless pixel compression methods are inefficient in handling diverse pixel formats and layouts, often requiring explicit sideband information and failing to achieve optimal compression rates, especially in mixed format scenarios.
Innovation Solution
The proposed solution involves detecting pixel formats and layouts within pixel memory regions, using embedded control information to select the most effective compression techniques and rearranging bytes into more homogeneous sub-regions, which are independently compressible and decompressable, and utilizing a multi-level applied compression table to simplify the compression process without needing sideband data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If explicit sideband information is used to indicate pixel formats, then format detection accuracy is improved, but data transmission overhead increases
Solution Approach 1:
The pixel data itself contains embedded format information that can be detected directly from the data stream without requiring separate sideband information. The system uses the pixel values and their arrangements to automatically determine the format and layout, making the data self-descriptive and eliminating the need for additional overhead bytes.
Solution Approach 2:
The patent extracts format detection logic directly from the pixel data stream by analyzing specific patterns and arrangements within the pixel values themselves. By taking out the format information embedded in the data structure and using it for compression decisions, the system avoids adding separate sideband information while maintaining accurate format detection.
2Adaptability or versatility
If multiple compression techniques are applied to handle diverse pixel formats, then compression adaptability is improved, but processing complexity increases
Solution Approach 1:
The patent segments the pixel data into distinct sub-regions based on detected format boundaries and characteristics. By dividing the data into homogeneous segments that can be independently compressed, the system handles diverse formats through a unified compression engine rather than requiring multiple specialized techniques, thus reducing processing complexity while maintaining adaptability.
Solution Approach 2:
The system dynamically adjusts compression parameters and techniques based on real-time analysis of pixel format characteristics. Rather than having fixed compression methods for each format, the compression engine adapts its behavior according to the detected data patterns, allowing a single dynamic system to handle multiple formats efficiently without the complexity of static multi-technique approaches.
3Productivity
If pixel data is rearranged into homogeneous sub-regions, then compression efficiency is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary format detection and sub-region identification during the compression process itself, rather than requiring a separate preprocessing step. By detecting formats and identifying homogeneous regions on-the-fly during compression, the system prepares the data for efficient compression without adding significant processing time, as the detection and compression occur in an integrated workflow.
Data Source
AI summary
A lossless pixel compressor may include technology to detect a format of a pixel memory region, and compress the pixel memory region together with embedded control information which indicates the detected format of the pixel memory region. Other embodiments are disclosed and claimed.