Hybrid Image Processing Segmentation for Quality and Speed
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Solution Overview
Problem
Conventional image processing systems face challenges in balancing image quality and resource efficiency, as hardware-based processing often results in cropped images and lower quality, while software-based processing leads to delays and increased latency.
Innovation Solution
A method that selectively uses software and hardware image processing based on the context of image areas, where hardware processing is applied to efficient areas and software processing is used for areas requiring higher quality or complex processing, such as borders and regions of interest, allowing for a seamless combination of processed pixels to generate a full-size output image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If hardware-based image processing is used, then processing speed is improved, but image quality deteriorates and image cropping occurs
Solution Approach 1:
The image processing is divided into multiple segments: hardware processing handles the majority of pixels for speed, while software processing handles border areas and regions of interest for quality. The image is effectively segmented into different processing zones that are handled by appropriate processing methods.
Solution Approach 2:
Different processing methods are applied to different regions of the image based on local requirements. High-quality software processing is applied locally to border areas and regions of interest, while hardware processing is used for the remaining areas where speed is more critical.
2Area of stationary object
If hardware size is minimized, then device size and cost are reduced, but processing capability deteriorates
Solution Approach 1:
The system achieves multi-functionality by combining hardware and software processing capabilities. The hardware processor handles routine processing, while the software processor provides enhanced processing for complex scenarios, making the system adaptable to various processing requirements without requiring separate dedicated hardware for each function.
Solution Approach 2:
The system dynamically selects processing methods based on the input image characteristics and processing requirements. The processor can switch between hardware-only, software-only, or combined processing modes, providing dynamic adaptability without requiring fixed dedicated hardware for each processing mode.
3Manufacturing precision
If software-based image processing is used, then image quality is improved, but processing latency increases
Solution Approach 1:
Software processing is applied partially only to the areas that require high quality (borders and regions of interest), rather than processing the entire image with software. This partial application of software processing maintains image quality where needed while minimizing the time penalty associated with software processing.
4Quantity of substance
If full-size image processing is implemented, then image storage capability is improved, but processing complexity increases
Solution Approach 1:
The processing complexity is segmented and distributed between hardware and software processing units. The hardware processor handles the bulk of the processing for full-size images, while the software processor handles only the complex border and region-of-interest processing, dividing the overall complexity into manageable parts.
Data Source
AI summary
A method for imaging processing is described. The method includes selecting a first set of image pixels of an input image and a second set of image pixels of the input image based at least in part on a context of the image pixels. Processing the first set of image pixels using hardware based processing to provide a first set of processed pixels is also included in the method. The method includes processing the second set of image pixels using algorithm based processing to provide a second set of processed pixels. The processed sets of pixels are combined to generate an output image. Apparatus and computer-readable media are also described.