Picture Coding Method Using Luminance Chrominance Ratio
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Solution Overview
Problem
Current picture coding methods are inefficient in compressing and decoding moving pictures, particularly due to the large amount of data required for high-quality video transmission, which results in clipping issues when coding is performed per block of 16 pixels, leading to incomplete output in display.
Innovation Solution
A method that selects the appropriate coding method based on the ratio of luminance to chrominance pixels, using variable length code tables to encode crop values and picture size data, allowing for efficient coding with fewer bits without compromising output accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If picture coding is performed per block of 16 pixels, then coding efficiency is improved, but clipping issues occur leading to incomplete output in display
Solution Approach 1:
The picture is divided into blocks of 16 pixels for coding, which improves coding efficiency. The patent applies segmentation by processing the picture in manageable blocks rather than as a whole, enabling efficient compression while managing the complexity of large picture data.
Solution Approach 2:
The patent applies local quality by differentiating between luminance and chrominance pixels in the block structure. By recognizing that luminance pixels require higher precision than chrominance pixels, the coding method can allocate bits differently across local regions, maintaining output accuracy for critical luminance information while allowing more aggressive compression for chrominance.
2Manufacturing precision
If high-quality video transmission is achieved, then picture quality is improved, but the amount of data increases resulting in transmission inefficiency
Solution Approach 1:
The patent applies parameter changes by exploiting the different importance weights of luminance and chrominance components. By changing the coding parameters differently for luminance pixels (requiring higher quality) versus chrominance pixels (allowing lower quality), the system achieves high picture quality where needed while reducing overall data amount through selective compression.
Solution Approach 2:
The patent applies partial action by not uniformly applying high-quality coding to all pixels. Instead, it concentrates coding resources on luminance pixels which are critical for picture quality, while applying more aggressive compression to chrominance pixels. This partial approach to quality maintenance significantly reduces data amount while preserving essential picture quality.
3Quantity of substance
If variable length code tables are used for encoding crop values, then bit usage is reduced, but coding complexity increases
Solution Approach 1:
The patent applies dynamics by using variable-length code tables instead of fixed-length codes. The code table dynamically adjusts the number of bits used to represent crop values based on their actual magnitude, using fewer bits for small values and more bits for larger values. This dynamic approach reduces overall bit usage while managing complexity through standardized variable-length coding schemes.
Data Source
AI summary
A picture coding method of the present invention codes a picture signal and a ratio of a number of luminance pixels and a number of chrominance pixels for the picture signal, and then one coding method out of at least two coding methods is selected depending on the ratio. Next, data related to a picture size is coded in accordance with the selected coding method. The data related to the picture size indicates a size of the picture corresponding to the picture signal or an output area, which is a pixel area to be outputted in decoding in a whole pixel area coded in the picture signal coding.