Adaptive Color Space Selection for Moving Picture Encoding
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Solution Overview
Problem
Existing moving picture encoding technologies face challenges in efficiently encoding RGB format data while maintaining prediction precision and controlling calculation complexity, particularly when dealing with the RGB format, as they often require transforming data into the YUV format, which can lead to reduced prediction precision and increased computational load.
Innovation Solution
An apparatus and method that dynamically determine whether to maintain the RGB format or transform into the YUV format based on the deviation of information in the R, G, and B components, using adaptive color transform techniques to select the most precise format for encoding, thereby optimizing prediction precision and reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If RGB format data is transformed into YUV format for encoding, then encoding compatibility is improved, but prediction precision deteriorates and calculation complexity increases
Solution Approach 1:
The patent applies dynamics by making the color space format selection adaptive rather than fixed. The encoding apparatus dynamically determines whether to use RGB or YUV format based on the deviation degree of R, G, and B components in each block, allowing the system to adapt to different image content characteristics and optimize prediction precision for each specific case
Solution Approach 2:
The patent changes the parameter of color space format (RGB or YUV) based on the deviation degree of color components. By calculating the deviation degree and comparing it against a threshold, the system selects the appropriate color space format, thereby improving prediction precision while maintaining encoding compatibility
2Adaptability or versatility
If RGB format data is transformed into YUV format for encoding, then encoding compatibility is improved, but calculation complexity increases
Solution Approach 1:
The patent applies local quality by performing the color space transformation selectively rather than uniformly across the entire image. Only blocks with low deviation degree (where YUV format is more suitable) undergo transformation, while blocks with high deviation degree maintain RGB format, thereby reducing overall calculation complexity while preserving encoding compatibility
Solution Approach 2:
The patent segments the image into multiple blocks and independently determines the color space format for each block based on its deviation degree. This segmentation allows the system to apply different encoding strategies to different regions, optimizing the balance between compatibility and computational load
3Measurement precision
If adaptive color transform is applied to each subblock, then prediction precision is improved, but device complexity increases
Solution Approach 1:
The patent applies partial action by performing adaptive color transform only on subblocks where it provides benefit. The system calculates deviation degree for each subblock and applies YUV transformation only when the deviation degree indicates it will improve prediction precision, avoiding unnecessary transformations and reducing device complexity
Data Source
AI summary
An apparatus for encoding a moving picture determines either an RGB format or a YUV format, in which intra prediction and inter prediction are executed based on a degree of deviation of information regarding each of R, G, and B components in moving picture data with the RGB format when a prediction selecting one component among three components in a color space format is designated in the input moving picture data with the RGB format, selects either color space format between the RGB format and the YUV format based on a determination result of the determination process, and executes orthogonal transform and quantization on the prediction error signal in the selected color space format and generating an encoded bit stream using a value subjected to the orthogonal transform and the quantization.