Lens-free imaging system and method

Abstract

The invention discloses a lens-free imaging system and method, belongs to the field of vehicle-mounted optical fiber communication, and aims to solve the problems of large size, high cost, limited imaging quality and the like caused by the fact that an existing imaging system depends on a lens. The system is only composed of the optical fiber array, the image sensor and other core components, low-loss direct optical coupling is achieved through the anti-resonance optical fiber array, a complex lens system is not needed for focusing, and the expensive design, manufacturing and assembly cost of a precise lens set is saved.

Description

Technical Field

[0001] This invention relates to the field of imaging system technology, and specifically to a lensless imaging system based on hollow anti-resonant optical fiber. Background Technology

[0002] Imaging systems play a crucial role in scientific research, medicine, industry, and consumer electronics. Traditional imaging systems, from mobile phone cameras to high-end microscopes, all rely on complex lens groups consisting of one or more lenses to focus light and form images. However, this lens-based architecture has inherent drawbacks: the presence of lens groups increases the system's size and weight, limiting its application in miniaturized and integrated devices (such as micro-drones and portable medical devices); furthermore, the high cost of manufacturing and assembling precision optical lenses drives up the overall system cost; additionally, lenses themselves introduce aberrations and dispersion, affecting the final image quality and requiring complex correction designs. Moreover, in applications such as automotive cameras, the lens surface is prone to moisture adhesion in rainy or foggy weather, or glare under strong light, severely affecting the accuracy of environmental perception and posing safety hazards. Summary of the Invention

[0003] The present invention aims to provide a lens-free imaging system and method based on hollow anti-resonant optical fiber, so as to solve the problems of large size, high cost and limited imaging quality caused by the reliance on lenses in existing imaging systems.

[0004] To achieve the above objectives, in a first aspect, the present invention proposes a lensless imaging system, characterized in that it comprises:

[0005] The light source module is used to emit light to illuminate an object to be imaged;

[0006] A hollow-core anti-resonant fiber array module is composed of a plurality of hollow-core anti-resonant fibers. The input end of the array module is used to receive light reflected or scattered from the object to be imaged.

[0007] An image sensor module is configured at the output end of the hollow anti-resonant fiber array module and is used to convert the optical signal transmitted through the multiple hollow anti-resonant fibers into electrical signal data containing spatial information.

[0008] A data processing module, connected to the image sensor module, is used to process the electrical signal data by executing an image reconstruction algorithm to generate an image of the object to be imaged.

[0009] In one possible implementation, the aforementioned lensless imaging system uses a narrow-bandwidth light-emitting diode (LED) light source or a laser light source as its light source module.

[0010] In one possible implementation, in the aforementioned lensless imaging system, the multiple hollow anti-resonant optical fibers in the hollow anti-resonant fiber array module are arranged in a rectangular array or an arc array.

[0011] In one possible implementation, in the aforementioned lensless imaging system, each of the hollow anti-resonant optical fibers comprises an air core and a multi-layer cladding structure surrounding the air core.

[0012] In one possible implementation, the aforementioned lensless imaging system uses a complementary metal-oxide-semiconductor image sensor module or a charge-coupled device (CCD) image sensor.

[0013] In one possible implementation, the image reconstruction algorithm executed by the data processing module in the aforementioned lensless imaging system includes at least one of the following steps: noise filtering, transmission deviation correction, and image reconstruction based on light intensity and / or phase information.

[0014] In one possible implementation, the aforementioned lensless imaging system uses an image reconstruction algorithm based on compressed sensing theory, a computational ghosting model, or a deep learning network.

[0015] Secondly, the present invention proposes a lens-free imaging method applicable to any of the systems described above, characterized by comprising the following steps:

[0016] Step S1: Light is emitted through the light source module to illuminate the object to be imaged;

[0017] Step S2: Receive the light reflected or scattered from the object using the input end of the hollow anti-resonant fiber array module, and transmit it through the fiber;

[0018] Step S3: Receive the transmitted optical signal using the image sensor module and convert it into electrical signal data;

[0019] Step S4: Receive the electrical signal data through the data processing module and run the image reconstruction algorithm to reconstruct the data into the final image of the object to be imaged.

[0020] Beneficial effects:

[0021] Extremely compact and lightweight structure: Since no lenses are needed for focusing, the system consists only of core components such as fiber arrays and image sensors, greatly reducing the system's size and weight. It allows light to be directly and efficiently coupled into the air fiber core from free space, eliminating the need for a complex pre-focusing optical system.

[0022] Low cost: It eliminates the design, manufacturing and assembly costs of expensive precision lens groups, and its manufacturing cost is advantageous compared to traditional special optical fibers, which greatly reduces the cost of the entire system.

[0023] High imaging quality: The air-core light guiding characteristics fundamentally avoid material absorption loss and nonlinear effects, achieving low-loss, high-fidelity transmission of optical signals. Combined with powerful back-end computational reconstruction algorithms, it can effectively correct deviations and suppress noise, obtaining high-resolution, high-contrast images.

[0024] Highly scalable: By changing the arrangement of hollow anti-resonant fibers (such as fiber spacing and array shape) or adjusting the reconstruction algorithm in the data processing module, a variety of special imaging functions can be flexibly realized, such as three-dimensional imaging, hyperspectral imaging, or imaging under specific environments. Attached Figure Description

[0025] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0026] Figure 1 This is the system structure and optical path diagram of an embodiment of the present invention.

[0027] Figure 2 This is a flowchart of the method in an embodiment of the present invention. Detailed Implementation

[0028] To provide a clearer understanding of the technical features, objectives, and effects of this invention, specific embodiments are now described with reference to the accompanying drawings, in which the same reference numerals denote the same parts. For the sake of simplicity, the parts related to this invention are shown schematically in each drawing and do not represent their actual structure as a product. Furthermore, for the sake of clarity and ease of understanding, in some drawings, components with the same structure or function are shown only schematically, or only one is labeled.

[0029] Regarding control systems, as is well known to those skilled in the art, functional modules and application programs (APPs) can take any suitable form, whether hardware or software, and can be multiple discrete functional modules or multiple functional units integrated onto a single hardware device. In its simplest form, the control system can be a controller, such as a combinational logic controller or a microprogrammed controller, as long as it can implement the operations described in this application. Of course, the control system can also be integrated as different modules onto a single physical device, without departing from the basic principles and scope of protection of this invention.

[0030] In this invention, "connection" can include direct connection, indirect connection, communication connection, electrical connection, unless otherwise specified.

[0031] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly specifies otherwise. It will also be understood that, when used in the specification, the terms “comprising” and / or “including” mean the presence of the stated features, values, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, values, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the listed related items.

[0032] It should be understood that the term "vehicle" or "of a vehicle" or other similar terms as used herein generally includes motor vehicles, such as passenger cars including sport utility vehicles (SUVs), buses, trucks, various commercial vehicles, boats including various vessels, aircraft, etc., and includes hybrid vehicles, electric vehicles, plug-in hybrid electric vehicles, hydrogen-powered vehicles, and other vehicles powered by alternative fuels (e.g., fuels derived from non-petroleum energy sources). As mentioned herein, a hybrid vehicle is a vehicle with two or more power sources, such as both gasoline and electric power.

[0033] Furthermore, the controller disclosed herein can be embodied as a non-transient computer-readable medium on a computer-readable medium containing executable program instructions that are executed by a processor, controller, or the like. Examples of computer-readable media include, but are not limited to, ROM, RAM, optical disc (CD)-ROM, magnetic tape, floppy disk, flash memory drive, smart card, and optical data storage device. Computer-readable recording media can also be distributed across a network-coupled computer system, such that the computer-readable media are stored and executed in a distributed manner, for example, via a telematics server or a controller area network (CAN).

[0034] Traditional single-mode optical fibers have very small mode field diameters, while common semiconductor lasers typically output beams with large divergence angles and spot sizes much larger than the mode field diameter of traditional single-mode fibers. If a beam with a large divergence angle and mismatched size is directly aimed at the micrometer-sized fiber core, most of the light will fail to couple, resulting in extremely high losses. Therefore, a lens assembly is needed to convert the divergent beam emitted by the laser into parallel light, and then precisely focus this parallel light into a very small spot (~10 μm) that matches the fiber core size, and inject it into the fiber at a matching angle. This process requires very precise mechanical adjustments, making the system complex, bulky, and sensitive to vibration.

[0035] Antiresonant fibers are typically designed to confine the vast majority (>99%) of optical energy within an air core. This air core can be made much larger in diameter than the solid core of conventional fibers (e.g., 20 μm, 30 μm, or even 50 μm), resulting in a correspondingly larger propagation mode (spot size). The large mode diameter of an antiresonant fiber (e.g., 30 μm) is very close to the output spot size of a conventional laser. The shape and size of the laser spot are almost identical to the mode the fiber itself intends to transmit. Therefore, the laser output head (which usually already has some collimation) can be simply brought close to and aligned with the end face of the antiresonant fiber, allowing light to couple directly into it with very low loss, without the need for complex lens systems for focusing.

[0036] This invention utilizes this characteristic of anti-resonant optical fibers. Light emitted from the light source module illuminates the object being imaged, and the reflected or scattered light enters the hollow-core anti-resonant fiber array module. The anti-resonant fiber array consists of tens of thousands of micrometer-sized optical fibers arranged regularly. Each fiber is an independent light transmission channel, corresponding to a pixel in the final image. The image of the object's surface is sampled by the end face (input face) of the imaging array, and the light intensity of each pixel is collected by the fiber directly opposite it. Due to the arrangement of the fiber array and the transmission characteristics of light within the fiber, fibers at different positions receive light information from different parts of the object. The light signal exits from the other end of the array (output face). The light intensity distribution pattern at the output end is completely consistent with the image at the input end, only pixelated. By placing a detector at the output end, this transmitted image can be received. Therefore, hollow-core anti-resonant optical fibers, utilizing their unique anti-resonant structure, can efficiently and with low loss transmit light to the image sensor module without the need for a complex lens system. The image sensor converts the received light signal into an electrical signal and transmits it to the data processing module. The data processing module processes these electrical signals according to a preset algorithm, and reconstructs the image of the object being imaged by analyzing information such as the intensity and phase of the light.

[0037] In Example 1, refer to Figure 1The system consists of the following core components:

[0038] The light source module is used to emit light to illuminate an object to be imaged;

[0039] When applied to automotive scenarios, the light source can employ a highly reliable automotive-grade infrared LED or laser diode array, with a center wavelength of 850nm or 940nm, to provide active illumination at night or in adverse weather conditions (such as dense fog or heavy rain), thereby enhancing environmental perception capabilities.

[0040] A hollow-core antiresonant fiber array module consists of multiple hollow-core antiresonant fibers. A single hollow-core antiresonant fiber comprises a hollow air core and a capillary cladding surrounding it. When light propagates in this fiber, the vast majority of its energy (>99%) is confined within the air core. Light guidance is achieved through the antiresonance effect between the cladding wall and the core mode, thereby significantly reducing material absorption and dispersion. The antiresonance effect efficiently confines light within the core, resulting in almost no loss. An array module is constructed by bundling and fusion-bonding hundreds to tens of thousands of such hollow-core antiresonant fibers into a single unit. The array's input end face is precision polished and directly faces the object to be imaged. Each fiber acts as a pixel acquisition channel, collecting light information from a corresponding tiny area on the object. Fiber array arrangements with specific field of view and resolution can be designed according to different automotive vision requirements (such as forward-looking, surround-view, and rear-looking). (For example, rectangular arrays are used for standard forward-looking, while curved arrays can be used for wide-angle surround-view.)

[0041] An image sensor module, configured at the output end of the hollow-core anti-resonant fiber array module, is directly coupled to the output end face of the fiber array or coupled through a micro-gap. It is used to convert the optical signals transmitted via the multiple hollow-core anti-resonant fibers into electrical signal data containing spatial information. In this embodiment, a high-resolution CMOS image sensor is used, for example, a CMOS sensor with a 2048x2048 pixel array and a 5.5μm pixel size. CMOS sensors have the advantages of high integration, low power consumption, and fast readout speed. The light spot array output from the fiber array is directly projected onto the photosensitive surface of the CMOS sensor, with each light spot corresponding to the output light intensity of one fiber.

[0042] A data processing module, connected to the image sensor module, processes the electrical signal data by executing an image reconstruction algorithm to generate an image of the object to be imaged. This module can be a high-performance computer, an embedded system, or a dedicated ASIC chip. It connects to the image sensor module via a high-speed interface (such as MIPI or USB 3.0). The core function of this module is to run the image reconstruction algorithm. Before system use, calibration is required: by acquiring the responses of a series of known patterns (such as a dot matrix), a transfer matrix describing the relationship between spatial points of the object and sensor pixel readings is established. During actual imaging, the data processing module first acquires the raw sensor data (i.e., the light intensity distribution of the fiber optic array), and then solves for the light field distribution of the original object by inverting the transfer matrix or using an iterative optimization algorithm (such as Tikhonov regularization), ultimately reconstructing a high-definition image. For more advanced applications, deep learning-based algorithms can be used to directly achieve end-to-end reconstruction from raw sensor data to a high-definition image by training a neural network (such as U-Net). This method has better performance in handling noise and artifacts.

[0043] In Example 2, refer to Figure 2 A lens-free imaging method is provided, and the workflow is as follows:

[0044] S1. Light illumination: The light emitted by the light source module is evenly illuminating the object to be imaged.

[0045] S2. Optical Information Acquisition and Transmission: Light reflected from different points on the surface of the object to be imaged enters different optical fibers in the hollow-core anti-resonant fiber array module corresponding to their spatial positions. Each fiber acquires the optical signal within its field of view and transmits it through a low-loss air core.

[0046] S3. Photoelectric signal conversion: After transmission, the light signal is emitted from the output of the array module, forming a light spot matrix, which is received by the image sensor module. The sensor converts the light intensity of each light spot into the corresponding pixel grayscale value, forming a frame of raw data.

[0047] S4. Calculation, Reconstruction, and Output: The raw data is transmitted to the data processing module. The data processing module calls the pre-calibrated transfer matrix and reconstruction algorithm to quickly process the data, ultimately reconstructing a clear, distortion-free image of the object, which can be displayed on the screen in real time.

[0048] In Example 3, an application of this system in a medical endoscope is provided:

[0049] Medical endoscopes are undergoing technological iterations from fiber optic endoscopes to electronic endoscopes, developing towards higher resolution, smaller size, and greater versatility. Rigid endoscopes play a crucial role in minimally invasive surgery, but are still limited by the size of traditional optical systems, restricting their access to narrower body cavities.

[0050] This embodiment integrates the hollow-core anti-resonant fiber array of the present invention into the front end of the endoscope probe, replacing the traditional objective lens. The key advantages of this design are: firstly, the diameter of the probe tip can be significantly reduced, allowing access to narrower cavities or blood vessels, thereby expanding the application range of minimally invasive surgery. Secondly, combined with a high-density fiber array and computational reconstruction algorithms, high-resolution imaging of tiny lesions, cells, or tissue structures can be achieved, providing doctors with pathological-grade diagnostic images. The hollow core fiber has a hollow channel inside, which brings unique extended functions. For example, while performing optical imaging, gas or liquid samples can be collected using the internal channel of the fiber, or a miniature sensing probe can be integrated, achieving multiple uses in one device and providing more comprehensive diagnostic information—something that no existing single-image endoscope can achieve.

[0051] Finally, it should be noted that the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application.

Claims

1. A lensless imaging system, characterized in that, include: The light source module is used to emit light to illuminate an object to be imaged; A hollow-core anti-resonant fiber array module is composed of a plurality of hollow-core anti-resonant fibers. The input end of the array module is used to receive light reflected or scattered from the object to be imaged. An image sensor module is configured at the output end of the hollow anti-resonant fiber array module and is used to convert the optical signal transmitted through the multiple hollow anti-resonant fibers into electrical signal data containing spatial information. A data processing module, connected to the image sensor module, is used to process the electrical signal data by executing an image reconstruction algorithm to generate an image of the object to be imaged.

2. The system according to claim 1, characterized in that, The light source module is a narrow-bandwidth light-emitting diode light source or a laser light source.

3. The system according to claim 1, characterized in that, The multiple hollow anti-resonant optical fibers in the hollow anti-resonant optical fiber array module are arranged in a rectangular array or an arc array.

4. The system according to claim 1, characterized in that, Each of the hollow anti-resonant optical fibers comprises an air core and a multi-layer cladding structure surrounding the air core.

5. The system according to claim 1, characterized in that, The image sensor module is a complementary metal-oxide-semiconductor image sensor or a charge-coupled device image sensor.

6. The system according to claim 1, characterized in that, The image reconstruction algorithm executed by the data processing module includes at least one of the following steps: noise filtering, transmission deviation correction, and image reconstruction based on light intensity and / or phase information.

7. The system according to claim 6, characterized in that, The image reconstruction algorithm is based on a computational ghosting model or a deep learning network.

8. A lens-free imaging method based on the system according to any one of claims 1 to 7, characterized in that, Includes the following steps: Step S1: Light is emitted through the light source module to illuminate the object to be imaged; Step S2: Receive the light reflected or scattered from the object using the input end of the hollow anti-resonant fiber array module, and transmit it through the fiber; Step S3: Receive the transmitted optical signal using the image sensor module and convert it into electrical signal data; Step S4: Receive the electrical signal data through the data processing module and run the image reconstruction algorithm to reconstruct the data into the final image of the object to be imaged.

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