Hybrid Predictor for Chrominance Spatial Predictive Coding
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Solution Overview
Problem
Conventional image coding methods require a large amount of calculation for spatial predictive coding of the chrominance component in intra-images, particularly due to the need for calculating vertical and horizontal variations and using plane prediction methods, which hampers compression efficiency.
Innovation Solution
A method and apparatus that calculate vertical and horizontal variations for a chrominance component, divide the image block into regions based on these variations, and use a hybrid predictor to generate prediction values, selecting the most efficient prediction method to minimize calculation and bit usage, thereby reducing the complexity of coding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If plane prediction method is used for chrominance component spatial predictive coding, then prediction accuracy is improved, but computational complexity increases significantly
Solution Approach 1:
The current block is divided into multiple prediction blocks (e.g., top and left regions), and different prediction methods are applied to different blocks. This segmentation allows the system to achieve high prediction accuracy in regions where it is needed while using simpler methods in other regions, thereby reducing overall computational complexity compared to applying plane prediction to the entire block.
Solution Approach 2:
Different prediction methods are selectively applied to different spatial regions of the chrominance component based on local characteristics. The hybrid prediction method uses DC prediction for some blocks and plane prediction for others, optimizing the balance between prediction accuracy and computational load for each local region rather than uniformly applying the complex plane prediction method everywhere.
2Productivity
If multiple prediction methods are evaluated to select the most efficient one, then compression efficiency is improved, but coding complexity increases
Solution Approach 1:
The patent performs preliminary evaluation of multiple prediction methods (DC prediction, vertical prediction, horizontal prediction, and plane prediction) by calculating prediction errors for each method before final encoding. This preliminary action allows the system to select the most efficient prediction method for each block, improving compression efficiency while managing coding complexity through systematic pre-evaluation rather than trial-and-error approaches.
3Device complexity
If DC prediction method is used for chrominance component, then computational load is reduced, but prediction accuracy deteriorates
Solution Approach 1:
The system dynamically selects between DC prediction and more complex prediction methods (such as plane prediction) based on the characteristics of each block. DC prediction is used for blocks where it provides sufficient accuracy with minimal computation, while plane prediction is applied to blocks requiring higher accuracy. This dynamic adaptation allows the system to optimize the balance between computational load and prediction accuracy on a block-by-block basis.
Data Source
AI summary
A method and apparatus for coding a chrominance component of an intra-image using spatial predictive coding and a method and apparatus for decoding the coded chrominance component are provided. The coding apparatus includes a variation calculator, which calculates a vertical variation and a horizontal variation with respect to a current block to be predictively coded among blocks having a predetermined size, into which a chrominance component of an input image is divided, using pixel values in an upper reference block adjacent to the current block and pixel values in a side reference block adjacent to the current block; a hybrid predictor, which divides the current block into a predetermined number of regions according to the vertical and horizontal variations and generates a prediction value of each pixel in each region using a pixel value in the upper reference block or a pixel value in the side reference block; a differential value generator, which generates a differential value between the prediction value and a corresponding real pixel value in the current block and codes the differential value using a predetermined coding method.