Imaging Architecture Memory Loop for Multi-Pass Pre-Processing
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Solution Overview
Problem
As camera pixel sizes decrease, existing imaging architectures require additional pre-processing steps, necessitating a more efficient method to normalize sensors and adapt to changing imaging conditions, while maintaining high power consumption and performance.
Innovation Solution
An imaging architecture that utilizes a memory module to store raw images, allowing for multiple pre-processing iterations through a loop formed by the memory module, compressor, and pre-processing block, using different parameter sets each time, with hardware pre-processing to achieve software-like benefits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If additional pre-processing steps are added to handle smaller pixel sizes, then image processing quality is improved, but device complexity and power consumption increase
Solution Approach 1:
The pre-processing function is segmented into multiple independent passes, where each pass performs a specific pre-processing operation (e.g., noise reduction, shading correction, dead pixel correction) on the raw image stored in memory. This allows the system to handle smaller pixel sizes with multiple targeted operations rather than requiring a single complex processing stage, thereby improving image quality while managing device complexity through modular processing.
Solution Approach 2:
The system performs preliminary pre-processing actions on the raw image before main processing by storing it in memory and running multiple pre-processing passes. This preliminary action prepares the image data in advance, reducing the burden on subsequent processing stages and enabling better handling of smaller pixel sizes without proportionally increasing overall system complexity.
2Manufacturing precision
If multiple pre-processing passes are implemented, then pre-processing quality is improved, but memory bandwidth and power consumption increase
Solution Approach 1:
The system creates a copy of the raw image in memory that can be processed multiple times without repeatedly accessing the sensor. This copying approach allows multiple pre-processing passes to be performed on the stored image data, improving pre-processing quality while avoiding the high power consumption that would result from multiple sensor reads and transfers.
Solution Approach 2:
The raw image is preliminarily stored in memory in a compressed or raw format before multiple pre-processing passes are applied. This preliminary storage action enables subsequent processing passes to operate on stationary data in memory rather than requiring continuous data transfer, thereby reducing memory bandwidth usage and power consumption while still allowing multiple processing iterations.
3Adaptability or versatility
If raw images are stored in memory for multiple processing passes, then processing flexibility is improved, but memory bandwidth requirements increase
Solution Approach 1:
The system copies the raw image data into memory once, creating a persistent storage copy that can be accessed and processed multiple times with different parameter sets. This single copy approach provides processing flexibility for multiple pre-processing passes while minimizing memory bandwidth consumption compared to approaches that would require repeated data transfers.
Solution Approach 2:
The stored raw image in memory serves multiple functions: it can be processed with different pre-processing parameter sets, used for statistics collection, and fed to different processing pipelines. This universal use of a single stored copy provides high processing flexibility while avoiding the need for multiple separate data storage paths, thereby reducing overall memory bandwidth requirements.
Data Source
AI summary
An imaging architecture has a memory module to store raw images for the pre-processing stage. The raw image from the output of the pre-processing block may be compressed by a compressor before the image is stored in the memory module. Furthermore, the raw image in the memory is subject to pre-processing as many times as needed or desired. Thus, a decompressor may be operatively connected to the memory module to retrieve the stored image and to decompress the retrieved image before providing the image to the pre-processing block. In the imaging architecture, a loop formed by the memory module, the decompressor, the pre-processing block and the compressor allows the image to be pre-processed multiple times. The imaging architecture can be coupled to the main processor and post-processor in an imaging device for further processing the image data for display or for transmission.