Block Mode Adaptive Motion Compensation for Mixed Mode Video Sequences
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Solution Overview
Problem
Existing motion compensated image processing technologies fail to accurately account for local characteristics of mixed mode image sequences, leading to artifacts and suboptimal picture quality, especially when handling image objects from different sources and varying motion phases.
Innovation Solution
A method and motion compensator that provide motion vectors and status information on a per-image-area basis, allowing for local motion compensation and de-interlacing, distinguishing between film and video modes, and adjusting processing accordingly to generate high-quality output image data with minimal hardware and memory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If global motion compensation is used for interlaced video sequences, then processing simplicity is maintained, but picture quality deteriorates due to inability to account for local characteristics of mixed mode sequences
Solution Approach 1:
The image is divided into multiple image areas (e.g., blocks or regions), and motion compensation is performed independently for each area based on its local characteristics. This allows the system to handle mixed mode sequences by identifying and processing film mode and video mode areas differently, thereby improving picture quality without requiring complete redesign of the processing architecture.
Solution Approach 2:
Different motion compensation strategies are applied to different image areas based on their local characteristics. Image areas identified as film mode receive processing appropriate for telecine sequences, while video mode areas receive processing optimized for interlaced video. This local adaptation resolves the contradiction by improving picture quality through localized processing without requiring complex global processing of the entire image.
2Measurement precision
If motion compensation is performed on a block basis for the entire image, then processing uniformity is maintained, but accuracy deteriorates due to inability to distinguish different motion phases in mixed mode sequences
Solution Approach 1:
The image is segmented into multiple image areas, and motion detection is performed independently for each area. This segmentation enables the system to detect different motion phases in different parts of the image, improving motion detection accuracy for mixed mode sequences while keeping the processing complexity manageable through modular block-based operations.
Solution Approach 2:
Motion detection and compensation parameters are determined locally for each image area based on its specific characteristics. This allows the system to accurately detect motion in film mode areas separately from video mode areas, resolving the contradiction between measurement precision and device complexity by applying localized analysis rather than uniform global processing.
3Manufacturing precision
If de-interlacing is performed without considering local image characteristics, then processing speed is maintained, but picture quality deteriorates due to artifacts in mixed mode sequences
Solution Approach 1:
The de-interlacing process is segmented into multiple stages: first identifying image areas with their respective modes (film or video), then applying appropriate de-interlacing algorithms to each area. This segmentation enables artifact-free processing of mixed mode sequences while maintaining processing speed through efficient block-based parallel processing.
Solution Approach 2:
Different de-interlacing algorithms are applied to different image areas based on their local characteristics. Film mode areas receive de-interlacing appropriate for telecine sequences, while video mode areas receive de-interlacing optimized for interlaced video. This local adaptation eliminates artifacts in mixed mode sequences without significantly reducing processing speed.
4Measurement precision
If status information is provided for the entire image, then processing overhead is minimized, but accuracy deteriorates due to inability to capture local motion characteristics
Solution Approach 1:
Status information (motion vectors, mode identification) is provided for each image area rather than for the entire image. This segmentation captures local motion characteristics accurately while keeping the total data amount manageable through efficient block-based representation and compression of motion information.
Solution Approach 2:
Motion information and status data are determined and stored locally for each image area, enabling accurate representation of local motion characteristics. This approach resolves the contradiction by providing sufficient motion information for accurate compensation without requiring excessive data, as each block only needs to store its own motion parameters rather than global image-wide parameters.
Data Source
AI summary
The present invention relates to a motion compensated image process taking local characteristics of image data into account. Image data included in a single image may stem from different video sources. In order to take specific motion phase into account, the motion compensation process is switched accordingly such that an improved picture quality can be achieved.