Adaptive Interpolation Filter Selection for Video Compression
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Solution Overview
Problem
Conventional video compression techniques, such as H.264/AVC, rely on a single preset interpolation filter, leading to inefficiencies in generating accurate prediction data for diverse images, especially in high-quality, large-capacity images, and result in high computation complexity.
Innovation Solution
An adaptive interpolation filter selection method that chooses from a filter bank based on context information like coding mode, quantization value, pixel position, and resolution of adjacent image blocks to generate a prediction block, reducing computation complexity and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single preset interpolation filter is used, then device complexity is reduced, but manufacturing precision deteriorates
Solution Approach 1:
The patent implements dynamic selection of interpolation filters based on image characteristics. The system evaluates whether the input image contains edges or textures and adaptively chooses between a first interpolation filter for edge/texture regions and a second interpolation filter for smooth regions. This dynamic adaptation resolves the contradiction by allowing the system to maintain low complexity through selective filter usage while achieving high prediction accuracy through context-appropriate filter selection.
Solution Approach 2:
The patent applies different interpolation filters to different regions of the image based on local characteristics. By detecting edge and texture information in specific regions and applying appropriate filters locally, the system achieves high prediction accuracy where needed while maintaining overall system simplicity. This local quality approach allows the system to optimize prediction performance without uniformly increasing complexity across the entire processing pipeline.
2Ease of operation
If a single preset interpolation filter is used, then ease of operation is improved, but productivity deteriorates
Solution Approach 1:
The system dynamically adjusts the interpolation process based on image content analysis. By automatically detecting whether regions contain edges or textures and selecting appropriate filters, the system maintains operational simplicity for the user while significantly improving compression efficiency through adaptive prediction. This resolves the contradiction by automating the complexity management internally while preserving ease of use externally.
Solution Approach 2:
The patent incorporates feedback mechanisms that analyze image characteristics (edge and texture information) and use this feedback to select appropriate interpolation filters. This feedback-driven approach allows the system to automatically optimize compression efficiency based on actual image content while maintaining simple operation for users. The feedback loop enables the system to adapt to different image types without requiring manual intervention.
3Manufacturing precision
If conventional interpolation is used for high-quality large-capacity images, then computation complexity increases, but manufacturing precision deteriorates
Solution Approach 1:
The patent segments the image processing task by dividing it into different regions based on edge and texture detection. By identifying and separating edge/texture regions from smooth regions, the system can apply specialized interpolation filters only where needed. This segmentation approach improves interpolation accuracy for complex image content while avoiding the computation complexity of applying complex filters uniformly across the entire image.
Solution Approach 2:
The system applies high-accuracy interpolation filters locally only to regions that require them (edge and texture regions), while using simpler filters for smooth regions. This local quality approach ensures high prediction accuracy where it matters most without incurring the full computation complexity cost across the entire image, thus resolving the contradiction between accuracy and computational burden.
Data Source
AI summary
The present invention relates to a method and to an apparatus for encoding and decoding images by adaptively using an interpolation filter in consideration of the characteristics of input images. The apparatus of the present invention comprises a prediction block-generating unit including a selector for adaptively selecting an interpolation filter for generating a prediction block in consideration of the context information of an input image block, a filter bank in which groups of interpolation filters are stored in correspondence with the context information, and a specific interpolation filter which is selected from the filter bank in accordance with the control of the selector, and which interpolates a reference image block associated with the input image block.