14 results about "Wavefront coding" patented technology

A wavefront coding and deep learning-based joint optimization image reconstruction method belongs to the technical field of image reconstruction, and aims to solve the problem of limited image reconstruction effect caused by independent processing of an image degradation process and an image reconstruction process in the prior art. The method comprises the following steps: building a decoding network model, preparing a data set, training a joint optimization network model, and testing an image reconstruction effect. Based on a collaborative optimization mechanism of a cubic phase coding plate and a deep neural network, wavefront coding parameters are introduced into a neural network training process by combining realizability of a cubic phase coding device, so that the wavefront coding parameters and network weight parameters are synchronously optimized. By guiding the input of the blurred image, more stable and consistent training input is provided for the deep learning network, and the convergence speed and generalization ability of the model are improved. And a decoding structure based on fusion of residual connection and an attention mechanism is adopted, so that the reconstruction precision and the visual quality are remarkably improved.

The invention discloses a wavefront coding microscopic system depth-of-field expansion joint optimization method based on deep learning, and belongs to the field of microscopic medical imaging, and the method comprises the steps: collecting a clear focusing image for neural network model training and testing; a defocusing phase is calculated according to corresponding optical system parameters, and defocusing blurring simulation is carried out on the clear focusing image; correcting a mask matrix by utilizing learnable aberration, and updating data in a training process to correct out-of-focus aberration; calculating a joint point spread function through the out-of-focus correction mask, and generating an out-of-focus correction image; and training a generative model by using a pair of the defocus correction image and the clear focusing image and a point spread function quality and image quality evaluation loss function, and recovering the optical image with high quality. According to the method, the free surface type of the mask is optimized, an optical physical mechanism is introduced to be fused with an image similarity evaluation function to form a model gradient return loss function, the aberration correction effectiveness of wavefront coding is ensured, and the imaging quality and robustness are improved.

The invention discloses a digital holographic depth-of-field extended imaging method and system based on wavefront coding, and the method comprises the steps: adjusting the parameters of all parts in a digital holographic microscopic system according to preset cubic phase parameters, and obtaining a candidate digital holographic microscopic system corresponding to the preset cubic phase parameters; adopting a candidate digital holographic microscopic system to image a preset category of target to obtain a first image; processing the first image by adopting a trained deep neural network corresponding to the candidate digital holographic microscopy system to obtain a second image; and acquiring second images corresponding to all candidate digital holographic microscopic systems, comparing all the second images, selecting the second image of which the image quality is greater than a threshold value, and taking the candidate digital holographic microscopic system corresponding to the second image as a final digital holographic microscopic system so as to image a preset category of target. According to the method, the depth-of-field extension optimization speed can be remarkably improved, and the storage space and computing resource consumption are reduced.

The invention discloses a non-contact vital sign monitoring system and method based on a mechanical programmable metasurface, and belongs to the technical field of intelligent medical monitoring. According to the system, 360-degree continuous phase regulation and control are achieved through the mechanical programmable metasurface, the three-dimensional dynamic beam focusing technology and the improved variational mode decomposition algorithm are combined, limb movement noise is effectively restrained, and high-precision multi-person non-contact respiration monitoring is achieved. The system adopts a modular detachable metasurface architecture, supports the fast reconstruction of wavefront coding, and can reduce the average error of respiratory rate monitoring of a human body in a double-arm swinging / walking state to 0.5 times / minute without continuous power supply. Experiments show that when the system is used for synchronously monitoring breathing signals of the motion state of two persons in a complex indoor environment, the signal-to-noise is improved by 14 dB or above compared with that of a traditional scheme, and the manufacturing cost is reduced by 77.5%. The method is suitable for the fields of intelligent old-age care, infectious disease isolation monitoring, sleep breathing disorder screening and the like, and the clinical requirements of medical privacy protection and long-term health monitoring are met.

The invention discloses an industrial machine vision-oriented strong backlight environment imaging sharpening system and method. The method comprises the following steps: S10, performing optical coding imaging; s20, carrying out improved L-R iterative recovery and first-stage wavelet denoising; s30, carrying out secondary wavelet denoising and fine recovery; and S40, carrying out iterative convergence and output. According to the invention, a specific wavefront coding optical imaging module and an improved L-R image restoration algorithm module are integrated into a complete visual detection system for solving the problem of industrial strong backlight imaging. In the L-R iteration process, a staged denoising step based on wavelet transformation is introduced, and before each iteration, first-level high-threshold wavelet denoising is carried out on a residual error; and in a specific stage in the iteration process, carrying out secondary middle threshold wavelet denoising on the current estimation image.

The invention discloses a high-angular-resolution wavefront measurement method and system based on random structure diffraction, and relates to the technical field of optical information measurement. According to the wavefront measurement method, phase modulation of incident light is realized by using a disordered diffractive optical element (DOE) in random binary phase distribution, and complex incident wavefront coding is realized through a Fresnel diffraction effect. The mapping relation between the diffraction pattern and the incident angle is further pre-calibrated through an experiment, and the wavefront to be measured is reconstructed in combination with a wavefront reconstruction algorithm. According to the scheme provided by the invention, the mapping relation between the DOE diffraction pattern and the incident angle is pre-calibrated through an experiment, accurate decoding of a local incident angle can be realized, a regional wavefront reconstruction algorithm is further combined, wavefront measurement with a large dynamic range, high spatial resolution and high angular resolution is satisfied, and the measurement precision is improved. And the method has higher reconstruction precision and real-time performance and better anti-noise capability.

The application discloses a high-resolution surface measurement method based on wide-spectrum laser and wavefront coding, which modulates the wavefront phase of a wide-spectrum laser light source, focuses the illumination light of different wavelengths on different heights of the normal direction of the surface of a measured object, receives the light radiation in the mirror normal direction of the normal of the surface of the measured object, determines the wavelength with the highest intensity according to the received light radiation, constructs a spectral dark spot distribution, successively illuminates the sample, performs one or more spectral dark spot positioning, determines the accurate central wavelength, and determines the height of the surface of the measured object according to the central wavelength. The light source uses wide-spectrum laser, so that the system light energy utilization is higher and the phase modulation is easier; the phase modulation is used to modulate the illumination light, which is beneficial to reducing the off-axis difference of the system to obtain higher resolution; and the spectral dark spot positioning method is beneficial to obtaining higher imaging positioning accuracy when the imaging signal is weak.

The invention discloses a wavefront coded image reconstruction method based on multi-scale deep learning, relates to the technical field of image reconstruction, and aims to solve the problem that dynamic blurred image reconstruction cannot be realized under the influence of a complex aerodynamic thermal effect caused by various flight conditions in the prior art, and the method comprises the following steps: obtaining an uncoded PSF and a coded PSF; making a data set; establishing a network model; model training; testing a reconstruction effect; according to the invention, through modulation of the wavefront coding technology, the image with the complex fuzzy degree is coded to the similar fuzzy level, the complexity of the image in the learning process is reduced, the reconstruction of the subsequent fuzzy image is facilitated, and the convergence of the model learning process is accelerated. Meanwhile, a mixed attention mechanism and multi-scale comparison are introduced, so that the learning process focuses on a key area of the image, and extraction of feature information by the network is optimized through continuous adjustment of weights; and meanwhile, the model is combined with multi-scale comparison, the features of the images under different scales are comprehensively learned, and the fine reconstruction capability of the blurred images is realized.

The utility model provides a camera lens device based on wavefront coding, and belongs to the technical field of optical detection. The camera lens device based on wavefront coding comprises a lens barrel and an industrial camera, the rear end of the lens barrel is connected with the industrial camera, an original infrared lens is installed in the lens barrel, a phase plate is fixed at the front end of the lens barrel, and a diaphragm is arranged between the phase plate and the original infrared lens. A phase plate is added, and the depth of field of the camera is expanded by using an encoding-decoding method, so that the measurement precision of the infrared deflection technology is improved; a wavefront coding method is adopted, so that the system is insensitive to defocus, and coding is realized by adding a phase plate into a camera lens; the phase plate is added, and the depth of field of the lens is expanded, so that in infrared deflection measurement, the camera can clearly image the measured lens and the light source, the position resolution and the angle resolution are improved, and the surface type reconstruction precision is improved.

The application discloses a wavefront coding microscopic system depth of field expansion joint optimization method based on deep learning, and belongs to the field of microscopic medical imaging. The application comprises the following steps: collecting clear focus images for neural network model training and testing; calculating defocus phases according to corresponding optical system parameters, and simulating defocus blur of the clear focus images; using a learnable aberration correction mask matrix, updating data to correct defocus aberration in the training process; calculating a joint point spread function through the defocus correction mask to generate a defocus correction image; using the defocus correction image and the clear focus image pair, and a point spread function quality and image quality evaluation loss function to train a generative model to generate a high-quality optical image. The application optimizes a mask free surface type, introduces an optical physics mechanism to fuse an image similarity evaluation function to form a model gradient back transmission loss function, ensures the effectiveness of wavefront coding aberration correction, and improves the imaging quality and robustness.

The application discloses an extended depth of field wavefront coding imaging system based on a cut-off sine mask. The system comprises a wavefront coding optical device, a detector and an image decoding device. The wavefront coding system introduces a new type of cut-off sine phase mask, and an object displays a coded image on the detector after passing through the wavefront coding optical device, and a clear image is obtained by decoding the coded image through the decoding device. The defocus phase is superimposed on a spatial light modulator to realize defocus measurement, and the method avoids high-precision manual displacement and can effectively expand the depth of field of an optical imaging system. A reflective spatial light modulator is arranged on a Fourier plane of the optical system to realize phase modulation of incident light waves. The system can reduce the center offset of a point spread function while expanding the depth of field range. Compared with a traditional cubic phase mask, the cut-off sine mask has significant advantages in reducing the center position offset, defocus stability and removing artifacts.

The present invention relates to a super-resolution imaging method and system, specifically a wavefront coding super-resolution imaging device, method, system, and storage medium, which overcome the two problems of original image data aliasing and the mismatch between the fused image and the adopted degradation function existing in existing sub-pixel staggered sampling super-resolution imaging technology. First, a sub-pixel staggered sampling wavefront coding image dataset is constructed; then, based on the sub-pixel staggered sampling wavefront coding image dataset, super-resolution reconstruction is achieved to obtain a super-resolution image; the imaging device includes a detector assembly and a wavefront coding lens fixed to the front end of the detector assembly; the wavefront coding theory is introduced into the sub-pixel staggered sampling super-resolution method, which not only achieves an improvement in resolution but also simultaneously achieves an extension of the depth of focus.

The invention provides a visible light near-infrared short wave refraction and reflection type wavefront coding athermalization imaging system, which belongs to the technical field of computer optical imaging, and comprises a primary mirror, a secondary mirror, a first lens, a second lens, an optical filter and a focal plane which are sequentially arranged from an object space to an image space, the primary mirror is used for realizing wavefront coding phase modulation of incident light, the secondary mirror is used for realizing wavefront coding phase modulation of incident light, the first lens and the second lens form a correction mirror group for realizing correction of residual aberration of the primary mirror and the secondary mirror, and the optical filter is used for realizing wavelength selection; and the focal plane is used for realizing imaging. The system is wide in wave band coverage range and covers visible light, near-infrared and short-wave infrared wave bands; the ratio of the total length to the focal length of the system is less than 0.25; the working temperature range is wide, the temperature range is-55 DEG C to + 70 DEG C, a focusing structure is not needed, and the system is miniaturized and light.

The present invention discloses an image restoration optimization method and system based on a strong light background, which relates to the technical field of image restoration. The main technical points of the present invention mainly include: realizing strong light background suppression through a wavefront coding system with a built-in mask plate, and collecting a coded image after background strong light suppression of an object to be detected; using an improved L-R image restoration algorithm to restore the coded image, and combining wavelet transform for residual iteration; and using a secondary threshold to remove two main types of noise and retain weak target data; on this basis, establishing a reference-free image quality evaluation system; and using a sliding window to calculate its arithmetic mean, and at the same time setting a patience iteration mechanism to control the effective iteration times of the L-R algorithm; finally, calculating the maximum value of the image evaluation parameters in each iteration to determine the optimal iteration times and obtaining a clear target image under a strong light background. The present invention can effectively eliminate the interference of a strong light background on target imaging, shorten the algorithm iteration time, restore the detail information of the target image under a strong light background, significantly improve the quality of the target image under a strong light background, and has excellent image restoration ability.