Multi-Pixel Memory Compositor for Video Scaling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional video data processing systems face inefficiencies in compositing images of different sizes, particularly in scaling processes, which affect processing speed, smoothness, and sharpness due to the large number of pixels involved.
Innovation Solution
A multi-pixel memory to memory compositor system that reads pixel data from memory, scales it using vertical or horizontal scalers, and merges the scaled data to achieve efficient image compositing, allowing for parallel processing and interpolation to maintain image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional raster operations are used for compositing images of different sizes, then image compositing can be achieved, but processing speed decreases due to the large number of pixels involved
Solution Approach 1:
The patent segments the image scaling process into multiple parallel processing units, each handling a portion of the pixel data simultaneously. This segmentation allows the system to process large numbers of pixels without a single sequential operation becoming a bottleneck, thereby improving processing speed while maintaining the ability to handle high-resolution images.
Solution Approach 2:
The patent introduces a multi-dimensional processing architecture that operates on pixel data across multiple dimensions simultaneously - temporal, spatial, and data-width dimensions. By processing pixels in parallel across multiple data paths and using interpolation techniques that operate on multiple samples simultaneously, the system achieves higher throughput without proportionally increasing the number of pixels to process.
2Adaptability or versatility
If scaling operations are performed to composite images of different sizes, then image compositing flexibility is improved, but processing throughput decreases
Solution Approach 1:
The patent implements dynamic scaling capabilities where the scaling factors and processing parameters can be adjusted in real-time based on the input image dimensions and desired output. This dynamic adaptation allows the same hardware architecture to efficiently handle various image sizes and compositing scenarios without requiring separate processing paths for each scale, thereby maintaining high throughput across different adaptability requirements.
Solution Approach 2:
The patent utilizes parameter changes in the interpolation process, where scaling operations are performed by adjusting interpolation coefficients and sample weights rather than performing pixel-by-pixel operations. This parameter-based approach to scaling maintains flexibility for different image sizes while improving throughput by reducing the computational complexity of each individual scaling operation.
3Productivity
If multiple instances of processing units are used to handle large pixel data, then processing capability is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple processing functions into a unified architecture where a single processing unit can handle multiple tasks through time-division and data-division techniques. Instead of using multiple separate instances of processing units, the system combines their functionality into one unit that processes different portions of pixel data at different times or through different data paths, thereby reducing overall device complexity while maintaining high pixel processing capability.
Solution Approach 2:
The patent designs a universal processing unit that can perform multiple functions including scaling, compositing, and color conversion through a single architecture. This multi-functional unit eliminates the need for separate dedicated hardware for each operation, reducing device complexity while maintaining the processing capability required for handling large pixel data volumes.
Data Source
AI summary
A method and system for processing video data using multi-pixel scaling in a memory system are provided. The multi-pixel scaling may include reading pixel data for one or more data streams from the memory system into one or more scalers, wherein each of the plurality of data streams includes a plurality of pixels, scaling the pixel via the one or more scalers and outputting the scaled pixels from the one or more scalers. Pixel data may be sequential or parallel. The plurality of scalers may be in parallel, scaling sequential pixel data with independent phase control, or scaling parallel pixel data in substantially equal phase. Pixel data may be transposed, replicated, distributed and aligned prior to reading by scalers, and may be aligned merged and transposed after scaling. Scaling may include interpolation or sub sampling using pixel phase, position, step size and scaler quantities.