Intra Prediction for Depth Images Using Boundary Segmentation
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Solution Overview
Problem
Current video processing technologies face inefficiencies in encoding and decoding 3D videos, particularly in predicting pixel values for depth images, which affect the encoding/decoding efficiency of 3D videos.
Innovation Solution
An intra prediction method is developed that determines pixel values in a prediction target block of a depth image by using boundary pixels and chain codes to split the block into regions, allowing for efficient prediction based on neighboring pixels, enhancing encoding/decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional intra prediction methods are used for depth images, then encoding/decoding process is simpler, but encoding/decoding efficiency is lower
Solution Approach 1:
The prediction target block is divided into multiple prediction target regions based on boundary pixels and chain codes. Each region is predicted separately using neighboring pixels specific to that region, allowing the algorithm to adapt to local depth variations while maintaining overall efficiency
Solution Approach 2:
Different prediction methods are applied to different regions within the prediction target block. By identifying boundary pixels and creating chain codes, the method applies localized prediction strategies that match the local depth characteristics, improving overall prediction accuracy without uniformly increasing complexity
2Measurement precision
If simple prediction methods are used, then processing speed is faster, but prediction accuracy is lower
Solution Approach 1:
Boundary pixels are identified and chain codes are generated before the actual prediction process. This preliminary segmentation allows the main prediction algorithm to work more efficiently by operating on pre-defined regions rather than searching for boundaries during prediction
Solution Approach 2:
The prediction method dynamically adapts to the local characteristics of depth images by using chain codes to represent boundary shapes. The prediction process adjusts to follow the actual geometry of depth boundaries, improving accuracy for complex shapes while maintaining speed through algorithmic optimization
3Loss of information
If conventional prediction methods are used, then processing is simpler, but compression performance is worse
Solution Approach 1:
The method changes the representation parameters by using chain codes to encode boundary pixel sequences. This parameter transformation allows efficient representation of complex boundary shapes, improving compression performance by better capturing the geometric characteristics of depth images
Solution Approach 2:
The boundary information is copied and represented through chain codes that can be efficiently transmitted and reconstructed. This copying mechanism allows the boundary geometry to be preserved with minimal bit rate overhead, improving compression efficiency
Data Source
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AI summary
The present invention relates to an intra prediction method for predicting pixel values within a prediction target block on the basis of a plurality of peripheral pixels adjacent to the prediction target block. The intra prediction method according to the present invention includes the steps of: receiving and decoding encoded image information; determining a target boundary by determining a plurality of boundary pixels representing the target boundary within the prediction target block on the basis of the decoded image information; determining a plurality of prediction target regions partitioned on the basis of the target boundary within the prediction target block; and performing a prediction for each of the plurality of prediction target regions on the basis of peripheral pixels differing from each other selected from among the plurality of the peripheral pixels.