Screen Content Dictionary Encoding and Decoding
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Solution Overview
Problem
Existing video codec standards face inefficiencies when encoding and decoding screen content, which often features repetitive patterns, leading to reduced quality and increased compression artifacts.
Innovation Solution
The implementation of 1-D, pseudo 2-D, and inter pseudo 2-D dictionary modes for encoding and decoding pixel values using previous pixel values stored in dictionaries, allowing for exact prediction without residuals, and the use of hash values to match current pixel values with previously encoded values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If normal video coding techniques are used to encode screen content with repetitive patterns, then the encoding process is simple, but the decoding quality deteriorates with compression artifacts
Solution Approach 1:
The patent uses dictionary modes to copy previously decoded pixel values and use them as predictions for current pixel values. Instead of encoding each pixel independently, the system identifies repeated patterns by comparing current pixels against a dictionary of previously decoded pixels, copying the reference pixel values and only encoding the differences (residuals). This approach is particularly effective for screen content with repetitive patterns like text and graphics, significantly improving decoding quality while maintaining encoding efficiency.
2Loss of energy
If compression is increased to reduce bit rate, then transmission cost decreases, but compression artifacts increase and quality deteriorates
Solution Approach 1:
The patent implements dictionary-based prediction where previously decoded pixel values are copied and used as predictions for current pixels. This reduces the amount of data that needs to be transmitted by only encoding the residuals (differences) rather than full pixel values. The copying mechanism enables higher compression ratios while maintaining quality because the residuals are much smaller and can be encoded more efficiently.
Solution Approach 2:
The patent changes the encoding parameter from encoding absolute pixel values to encoding prediction residuals. By transforming the data representation from original pixel values to differences between predicted and actual values, the system achieves better compression efficiency. The residual values have smaller magnitudes and can be quantized more coarsely without significant quality loss, thereby reducing transmission cost while preserving content quality.
3Loss of information
If dictionary modes are used to improve encoding efficiency, then the number of bits required decreases, but the device complexity increases
Solution Approach 1:
The patent segments the encoding process into distinct stages: dictionary population (collecting previously decoded pixels), pattern matching (comparing current pixels against the dictionary), residual calculation (computing differences), and entropy coding (compressing the residuals and mode indicators). This segmentation allows each component to be optimized independently and makes the overall complex process more manageable and implementable in hardware or software.
Solution Approach 2:
The patent performs preliminary actions by pre-populating a dictionary with previously decoded pixel values before encoding the current block. This preliminary dictionary construction enables efficient pattern matching during the actual encoding process, as the comparison data is already prepared and organized. The preliminary action of building the dictionary once and reusing it across multiple encoding operations reduces the per-block encoding complexity while maintaining high compression efficiency.
Data Source
AI summary
Innovations are provided for encoding and/or decoding video and/or image content using dictionary modes. For example, some innovations predict current pixel values from previous pixel values stored in a 1-D dictionary. Other innovations predict current pixel values from previous pixel values using a pseudo 2-D dictionary mode. Yet other innovations predict current pixel values from previous pixel values in a reference picture using an inter pseudo 2-D dictionary mode. Pixel values can be predicted from previous pixel values (e.g., stored in a dictionary) that are identified by an offset and a length. Yet other innovations encode pixel values using hash matching of pixel values.