Holographic Imaging System Volume Segmentation

The patent divides the large target volume into multiple smaller sub-volumes and processes them separately. This segmentation allows the system to handle large volumes by breaking them into manageable chunks, reducing the computational complexity and memory requirements while maintaining the ability to image entire large spaces.

The patent transitions from conventional 2D imaging to 3D volumetric imaging by adding the depth dimension through time-of-flight measurements. This dimensional expansion enables scanning of large volumes while using holographic interferometry to extract three-dimensional information from the reflected radio waves.

The patent pre-calculates and stores projection operators and aggregation operators before actual imaging occurs. These pre-computed operators are reused during the imaging process, significantly reducing the real-time computational burden while maintaining high measurement precision through accurate projection and aggregation operations.

The patent uses holographic field data to create virtual copies of the target volume and its sub-volumes. By working with these computational copies rather than direct measurements, the system can perform multiple analysis passes and iterations without additional physical measurements, reducing overall computing power requirements.

The patent implements a dynamic processing approach where the system can adaptively adjust the number and size of sub-volumes based on the total target volume being scanned. This dynamic configuration allows the same system to efficiently image both small and large volumes by optimizing the segmentation parameters for each specific application.

The patent creates a universal imaging system that can handle various volume sizes through the use of scalable sub-volume decomposition. The same core algorithms and processing pipeline work for both small and large volumes, making the system versatile across different application scenarios without requiring separate specialized systems.

The patent performs computationally intensive operations in advance, including calculating projection operators, aggregation operators, and other transformation matrices before actual imaging takes place. This preliminary computation shifts the high energy consumption to an offline setup phase, allowing the actual imaging operation to run with much lower power requirements while maintaining high detection accuracy.

The patent changes the processing parameters by using pre-computed operators with optimized data structures and formats. By transforming the raw holographic data through these pre-configured operators, the system achieves high measurement precision with reduced computational effort during the actual imaging phase, thereby lowering operating costs.