Projection-Based Image Data Compression Orthogonal Residuals
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Solution Overview
Problem
Current block-based coding techniques for image data compression, such as those used in the H.264 standard, face inefficiencies in energy management and information loss during quantization, particularly when dealing with residual data blocks that are not orthogonal to reference blocks.
Innovation Solution
The technique involves scaling a reference block by a projection factor calculated based on the current block, ensuring the scaled reference block is orthogonal to the residual block, which reduces energy and improves compression efficiency by minimizing information loss during quantization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If block-based coding techniques are used for image data compression, then compression can be achieved through standard processes, but energy is not efficiently managed and information loss occurs during quantization
Solution Approach 1:
The patent applies preliminary action by performing a projection operation on the reference block before subtraction. The reference block is projected onto the residual block using a projection factor calculated from their inner product, ensuring the projected reference block is orthogonal to the residual block. This preliminary orthogonalization reduces the energy of the residual block before quantization, thereby minimizing information loss during the subsequent quantization process.
Solution Approach 2:
The patent changes the parameter of the reference block by applying a projection factor to scale it. The projection factor is calculated as the inner product between the reference block and the current block, and this scaling transforms the reference block into a form that is orthogonal to the residual block. This parameter transformation optimizes the energy distribution, reducing residual energy and improving quantization efficiency.
2Productivity
If reference blocks are used for prediction, then compression efficiency can be improved, but the residual block energy remains high causing information loss
Solution Approach 1:
The patent applies preliminary action by performing a projection operation on the reference block before subtraction. The reference block is projected onto the residual block using a projection factor calculated from their inner product, ensuring the projected reference block is orthogonal to the residual block. This preliminary orthogonalization reduces the energy of the residual block before quantization, thereby minimizing information loss during the subsequent quantization process.
Solution Approach 2:
The patent uses feedback by calculating the projection factor based on the inner product between the reference block and the current block, then using this factor to scale the reference block. This feedback mechanism ensures that the scaled reference block adapts to the actual content of the current block, improving prediction accuracy and reducing residual energy while maintaining compression efficiency.
Data Source
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AI summary
Methods, systems, and computer programs for encoding and decoding image are described. In some aspects, an input data block and a prediction data block are accessed. A projection factor is generated based on a projection of the input data block onto the prediction data block. A scaled prediction data block is generated by multiplying the projection factor by the prediction data block. A residual data block is generated based on a difference between the input data block and the scaled prediction data block. In some aspects, a prediction data block, a residual data block, and a projection factor associated with the residual data block are accessed. A scaled prediction data block is generated by multiplying the projection factor by the prediction data block. An output data block is generated by summing the residual data block and the scaled prediction data block.