Image Rotation Using HSRAM for Real-Time Embedded Displays
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Solution Overview
Problem
Embedded systems face challenges in efficiently rotating high-definition images due to limited computing resources, particularly when images need to be oriented correctly for display on various devices.
Innovation Solution
A method and system that partitions image data into portions, rotates each portion individually using high-speed random access memory (HSRAM), and assembles the rotated portions to create a correctly oriented image for display, utilizing a fast local rotation module and high-speed random access memory (HSRAM) for efficient image rotation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image rotation is performed on high-definition images in embedded systems, then image orientation accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The patent divides the image into multiple smaller portions (e.g., 8x8 pixel blocks) and processes each portion independently through the rotation module. This segmentation reduces the computational complexity of rotating large high-definition images while maintaining overall orientation accuracy, as each small portion is rotated and then reassembled to form the complete rotated image.
Solution Approach 2:
The patent performs preliminary actions by pre-processing image data into portions and preparing rotation parameters before actual rotation execution. The system pre-calculates rotation matrices and prepares memory buffers for rotated portions, enabling faster execution during real-time processing and reducing overall processing time.
2Productivity
If image rotation is performed in real-time for video streaming, then responsiveness is improved, but computational resources are exhausted
Solution Approach 1:
The patent segments the image processing task into smaller independent operations on image portions, which can be processed in parallel or sequentially with reduced computational burden. This segmentation enables real-time processing by reducing the complexity of each individual rotation operation while maintaining overall processing speed.
Solution Approach 2:
The patent uses memory buffers to store rotated portions temporarily before assembling the final image. This copying mechanism allows the system to perform rotation operations without immediately writing to the final output, enabling batch processing and reducing real-time computational pressure on the embedded system.
3Speed
If high-speed random access memory (HSRAM) is used for image rotation, then rotation speed is improved, but memory capacity constraints are worsened
Solution Approach 1:
The patent divides the image into small portions that can be stored in and processed by HSRAM. By segmenting the image data, the system only needs to load and process small portions in HSRAM at a time, rather than loading the entire high-definition image, thus overcoming HSRAM's limited capacity while maintaining high rotation speed.
Solution Approach 2:
The patent performs rotation operations on partial image portions rather than the complete image. This partial action approach allows the system to utilize HSRAM's high speed for processing small data chunks efficiently, achieving fast rotation speed without requiring HSRAM to hold the entire large image, thus working around the memory capacity limitation.
Data Source
AI summary
A method and apparatus for real-time image adjustment are disclosed, particularly suited for embedded systems with limited computing resources. The method involves selecting a target area within an image, partitioning this area into multiple portions, and utilizing a random access memory (RAM) to facilitate the rotation of each portion. The rotated portions are then assembled to form a complete, rotated target area, which is subsequently displayed on an image consumer device. This process is optimized for efficiency and speed, ensuring that high-definition images can be processed and oriented correctly in real time.