Super-resolution ghost imaging method and system based on partial Hadamard matrix

A low-resolution image and high-resolution image technology is applied in the field of computational ghost imaging method and system based on partial Hadamard measurement super-resolution, and can solve the problems of unsatisfactory imaging effect, redundant information, and increased imaging time, etc. Achieve the effect of shortening imaging time, reducing the amount of data storage, and reducing the number of measurements

Active Publication Date: 2020-10-27
NORTHWEST UNIV(CN)
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, this method still uses random under-sampling when collecting light intensity information. The possibility of information overlap is high, the sampling efficiency is low, and there is redundant information. The increase in the sampling rate greatly increases the imaging time, so the imaging The effect is not ideal

Method used

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  • Super-resolution ghost imaging method and system based on partial Hadamard matrix
  • Super-resolution ghost imaging method and system based on partial Hadamard matrix
  • Super-resolution ghost imaging method and system based on partial Hadamard matrix

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Experimental program
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Effect test

Embodiment 1

[0043] This embodiment proposes a method for constructing a super-resolution model, and the specific steps are as follows:

[0044] Step 1: Perform enhancement processing on any known high-resolution image set to expand the image set;

[0045] Step 2: performing downsampling at different magnifications on the image set obtained after the enhancement processing in step 1 to obtain a downsampled image set, that is, a low-resolution image set;

[0046] The downsampled image set is a downsampled image corresponding to the images in the image set obtained after the enhancement process;

[0047] Step 3: Perform blur kernel noise processing on the down-sampled image set obtained in step 2 to obtain a noisy low-resolution image set; considering that there will be noise interference in the ghost imaging experiment process, so add blur kernel noise (defocus blur, motion blur, Gaussian noise) to generate low-resolution images;

[0048] Step 4: The enhanced image set obtained in step 1 ...

Embodiment 2

[0057] This embodiment provides a super-resolution ghost imaging method based on a partial Hadamard matrix, including the following steps:

[0058] Step (1): Randomly select M rows from the partial Hadamard matrix of N×N size to form M The size of the measurement matrix, M, N are natural numbers and M≤N:

[0059] First, the computer generates a partial Hadamard measurement matrix of N×N size through matlab software, and reshape each column of the measurement matrix as The size of the measurement matrix, to obtain M matrices;

[0060] Step (2): Spatial light adjustment is performed on the M measurement matrices, and light spots corresponding to the measurement matrices are generated and projected onto the object to be imaged to collect light intensity information, and M light intensity information is obtained:

[0061] Send it to the spatial light modulator, and the light passes through the spatial light modulator to generate correspondingly distributed light spots and proj...

Embodiment 3

[0066] This embodiment provides a super-resolution ghost imaging system based on a partial Hadamard matrix, including: a computer, a spatial light modulator, a single-pixel detector, and a data acquisition module;

[0067] The computer includes the super-resolution model based on the confrontation network, which is used to store part of the Hadamard matrix and generate a measurement matrix;

[0068] The spatial light modulator is used to process the above-mentioned measurement matrix to generate correspondingly distributed light spots and project them onto the object to be imaged;

[0069] The single-pixel detector is used to detect the light intensity information on the object to be imaged;

[0070] The data collection module is used to collect light intensity information detected by a single-pixel detector, and upload it to a computer to obtain a low-resolution image;

[0071] The computer is also used to obtain a high-resolution image of the object to be imaged by performi...

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Abstract

The invention discloses a super-resolution ghost imaging method and a super-resolution ghost imaging system based on a partial Hadamard matrix, aiming at overcoming the defect of large data acquisition quantity of the original ghost imaging system. The partial Hadamard matrix is used for replacing random light spots of the original ghost imaging system, and a super-resolution processing link is added into the system. According to the system, the measurement method is optimized during acquisition, so that the required data acquisition amount and storage amount for common objects are relativelysmall, the calculation amount during preliminary imaging is relatively small, and the imaging time is short. After a proper super-resolution processing method is adopted for processing, a clear imagecan be obtained by quickly processing a preliminary result. The method can be applied to underwater and remote sensing complex scenes with poor imaging effects in a plurality of traditional imaging modes.

Description

technical field [0001] The invention belongs to the field of image detection and image recognition, and in particular relates to a super-resolution calculation ghost imaging method and system based on partial Hadamard measurements. Background technique [0002] The principle of ghost imaging is to use the second-order correlation of the light field to obtain the imaged scene or object, so multiple measurements are required. The previous method is to image the light intensity information generated by projecting random light spots, but due to the strong correlation between random light spots, a large number of measurements are required to obtain a good result. [0003] Currently, compressed sensing is widely used in ghost imaging technology. Due to the shortcomings of directly using the compressed sensing algorithm, such as large amount of calculation and long imaging time, the method of combining compressed sensing and deep learning for ghost imaging has appeared in recent y...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40G06T5/00G06N3/04G06N3/08
CPCG06T3/4053G06T3/4046G06T5/002G06N3/08G06N3/045
Inventor 乐明楠李璐祝轩范建平樊萍李展艾娜张薇张二磊
Owner NORTHWEST UNIV(CN)
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