MicroCloud Hologram (NASDAQ:HOLO) Realizes the 3D Holographic Reconstruction of Single-Photon LiDAR Data

Rhea-AI Summary

MicroCloud Hologram Inc. (NASDAQ: HOLO) has developed an advanced point cloud denoising algorithm for real-time 3D holographic reconstruction of single-photon LiDAR data. This algorithm enhances IP protection and technological competitiveness. Traditional computational algorithms often lag in speed and detail, but HOLO's solution delivers robustness and scalability, processing tens of frames per second. The technology supports autonomous navigation and environmental detection, showing superiority over traditional LiDAR with low power consumption and high sensitivity. HOLO aims to advance the adoption of autonomous driving technologies, serving numerous clients in the new energy vehicle sector.

Positive

• Development of a new point cloud denoising algorithm for real-time 3D holographic applications.
• Enhances intellectual property protection and technological competitiveness.
• The algorithm processes tens of frames per second, improving operational efficiency.
• Offers advantages over traditional LiDAR, such as low power consumption and high sensitivity.

Negative

• None.

BEIJING, Jan. 20, 2023 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO) ("HOLO" or the "Company"), a Hologram Digital Twins Technology provider, today announced that it developed a point cloud denoising algorithm for the real-time 3D holographic reconstruction of single-photon LiDAR data. The algorithm is the result of the Company's independent research and development, which is conducive to further improving the Company's intellectual property protection system, maintaining its technological leadership, and enhancing its core competitiveness.

Although 3D holographic LiDAR point cloud imaging continues to evolve rapidly, currently available computational imaging algorithms are often too slow, insufficiently detailed, or require extremely high arithmetic power, and even CNN-based (convolutional neural network) algorithms for estimating scene depth struggle to meet real-time requirements after training. HOLO proposes a new algorithm structure that meets the requirements of speed, robustness, and scalability. The algorithm applies a point cloud denoising tool for computer graphics and can efficiently model the target surface as a 2D manifold embedded in 3D space. This algorithm can merge information about the observed model, such as Poisson noise, the presence of bad pixels, compressed sensing, etc. This algorithm also uses stream modeling tools for computer graphics and can process tens of frames per second by selecting massively parallel noise reducers. HOLO's algorithm consists of three main steps: depth update, intensity update, and background update.

Depth update: Gradient steps are taken for depth variables with point clouds denoised using the point set surface algorithm. The update is operated in a coordinate system in 3D holographic space. Adaptation is performed on smooth continuous surfaces under the control of the kernel. In contrast to conventional depth image denoising, HOLO's point cloud denoising can handle an arbitrary number of surfaces per pixel, regardless of the format. In addition, all 3D points are processed in parallel, resulting in short computing times. In addition, all 3D points are processed in parallel, significantly reducing computing time.

Intensity update: Gradient steps are taken by targeting the coordinates of individual pixels in 3D holographic space to reduce noise. In this way, only the correlation between points within the same surface needs to be considered. The nearest low-pass filter is used for each point. This step considers only local correlations and processes all points in parallel. After the denoising step, points below a given intensity threshold, i.e., the minimum permissible reflectance, are removed.

Background update: This depends on the characteristics of the LiDAR system and is similar to intensity and depth updates. In a double-Bragg-grating scanning system, the laser source and the single photon detector are not coaxial, and the background counts are not necessarily spatially correlated. Therefore, no spatial regularization is applied to the background, in which case the noise reduction operation is simplified to a constant equation. Background detection is similar to passive images in single-Bragg-grating scanning systems and LiDAR arrays. In this case, spatial regularization helps to improve the estimated value. Therefore, an off-the-shelf image-denoising algorithm with low computational complexity can be used.

HOLO's real-time 3D holographic reconstruction based on single photon data adopts a new computational framework. This framework allows the 3D reconstruction of complex outdoor scenes with a processing time of about 10-20 milliseconds by combining statistical models with highly expandable computational tools of computer imaging technology. The algorithm developed by HOLO can handle every pixel surface, allowing target detection and imaging in complex scenes. It also enables stable real-time target reconstruction of complex moving scenes, paving the way for implementing video-rate single photon LiDAR technology for 3D holographic imaging applications.

3D holographic scene reconstruction has many applications, such as autonomous navigation and environmental detection. It has several subdivision fields, such as RGB-D sensors for emissivity imaging, stereo imaging, or full waveform LiDAR 3D holographic imaging. HOLO's single photon LiDAR technology solution has several outstanding advantages over traditional solutions. It is a safe laser light source with low power consumption and high sensitivity and enables the reconstruction of high fractional 3D holographic images in high scattering underwater environments or extremely foggy environments.

HOLO has been an industry leader in point cloud algorithms for holographic LiDAR and a service provider for many well-known new energy vehicle companies, as well as ADAS vehicle control system integrators and device developers. HOLO cooperates with automotive manufacturers in exploring advanced technologies and is seeking comprehensive digital sensing solutions to accelerate and scale the adoption of its autonomous driving technologies. HOLO's holographic LiDAR leverages this market trend to provide an excellent solution for large-scale autonomous driving mass production.

About MicroCloud Hologram Inc.

MicroCloud Hologram Inc. (NASDAQ:HOLO) engages in the research and development, and application of holographic technology. MicroCloud Hologram technology services include holographic light detection and ranging (LiDAR) solutions based on holographic technology, holographic LiDAR point cloud algorithms architecture design, technical holographic imaging solutions, holographic LiDAR sensor chip design, and holographic vehicle intelligent vision technology to service customers that provide holographic advanced driver assistance systems (ADAS). MicroCloud Hologram provides its holographic technology services to its customers worldwide. MicroCloud Hologram also provides holographic digital twin technology services and has a proprietary holographic digital twin technology resource library. MicroCloud holographic digital twin technology resource library captures shapes and objects in 3D holographic form by utilizing a combination of holographic digital twin software, digital content, spatial data-driven data science, holographic digital cloud algorithm, and holographic 3D capture technology.

Safe Harbor Statements

This press release contains "forward-looking statements" within the meaning of the Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified by terminology such as "will," "expects," "anticipates," "future," "intends," "plans," "believes," "estimates" and similar statements. Statements that are not historical facts, including statements about the Company's beliefs and expectations, are forward-looking statements. Among other things, the business outlook and quotations from management in this press release, as well as the Company's strategic and operational plans, contain forward−looking statements. The Company may also make written or oral forward−looking statements in its periodic reports to the U.S. Securities and Exchange Commission ("SEC") on Forms 20−F and 6−K, in its annual report to shareholders, in press releases and other written materials and in oral statements made by its officers, directors or employees to third parties. Forward-looking statements involve inherent risks and uncertainties. A number of factors could cause actual results to differ materially from those contained in any forward−looking statement, including but not limited to the following: the Company's goals and strategies; the Company's future business development, financial condition and results of operations; the expected growth of the AR holographic industry; and the Company's expectations regarding demand for and market acceptance of its products and services. Further information regarding these and other risks is included in the Company's annual report on Form 20-F and current report on Form 6-K and other documents filed with the SEC. All information provided in this press release is as of the date of this press release, and the Company does not undertake any obligation to update any forward-looking statement, except as required under applicable laws.

 

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SOURCE MicroCloud Hologram Inc.

FAQ

What is MicroCloud Hologram's new algorithm about?

MicroCloud Hologram has developed a point cloud denoising algorithm for real-time 3D holographic reconstruction, enhancing processing speed and robustness.

How does HOLO's technology improve LiDAR applications?

HOLO's technology allows for efficient 3D reconstruction of complex scenes, notably improving performance in autonomous navigation and environmental detection.

What are the key benefits of HOLO's point cloud denoising algorithm?

Benefits include faster processing times, improved image quality, and better adaptation to complex outdoor environments.

What sectors can benefit from HOLO's technology?

HOLO's technology has applications in autonomous navigation, environmental detection, and advanced driver assistance systems (ADAS) for vehicles.

What competitive advantages does HOLO's algorithm offer?

HOLO's algorithm boasts low power consumption, high sensitivity, and better performance in challenging conditions compared to traditional LiDAR solutions.