DS-CDMA Compression for Array Camera Power Reduction
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Solution Overview
Problem
Array cameras face significant power consumption challenges due to high pixel capacity and data processing requirements, as every pixel must be processed to create a read-out compressed data stream, straining system resources and increasing power usage.
Innovation Solution
Implementing direct sequence code division multiple access (DS-CDMA) for immediate compression of array camera data streams, allowing only one numerical operation per pixel and separating image data processing between the camera head and post-processing, reducing the need for buffering and processing steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing is applied to every pixel in array cameras, then complete image data is captured, but power consumption increases significantly (10 nanojoules per pixel)
Solution Approach 1:
The patent applies partial action by processing only a subset of pixels rather than all pixels. Scene analysis is performed on compressed or low-resolution format containing a portion of pixel data, and only selected pixels requiring analysis are processed at high resolution. This reduces power consumption while maintaining sufficient image quality for the application.
Solution Approach 2:
The patent segments the image processing task into two stages: (1) scene analysis on compressed/low-resolution data to determine which pixels need processing, and (2) selective processing of only those identified pixels at high resolution. This segmentation allows the system to avoid processing all pixels while still capturing necessary image information.
2Loss of information
If all captured pixels are processed and displayed, then complete image information is provided, but processing time and computational resources increase
Solution Approach 1:
The patent processes only the minimum necessary pixels required to convey the essential scene information. By analyzing compressed/low-resolution data first, the system identifies and processes only those pixels that contain meaningful information, avoiding unnecessary processing of redundant pixels while maintaining image information completeness.
Solution Approach 2:
The patent performs preliminary scene analysis on compressed or low-resolution format before processing high-resolution components. This preliminary action identifies which pixels require detailed processing, allowing the system to prepare and prioritize processing tasks in advance, thereby reducing overall processing time.
3Use of energy by moving object
If minimal processing is performed in camera head, then power consumption is reduced, but compression performance may be compromised
Solution Approach 1:
The patent segments compression operations into minimal processing in the camera head (applying code division multiplexing) and more sophisticated compression algorithms performed later during post-processing. This segmentation allows the camera head to operate with minimal power consumption while the overall system achieves good compression performance through subsequent processing stages.
Solution Approach 2:
The patent introduces code division multiplexing as an intermediary technique that enables efficient data representation with minimal processing. By modulating pixel data streams with codes and combining them, the system achieves effective compression at the sensor level with minimal power consumption, while allowing for further compression enhancement in post-processing.
Data Source
AI summary
Aspects of the present disclosure describe systems, methods, and structures for improved compression of array camera image data and improved power budgets for array cameras.