Analyzing the difference in image quality between different ghost imaging systems using a unified optical transfer function

Digit classification of ghost imaging based on similarity measures

Optical imaging systems are widely used in various video surveillance sites, which may endure various harsh environmental aging conditions such as salt mist, change of temperature. However, there are few studies on the impact of various environmental tests on the overall imaging performance of the system. In this paper, several common environmental tests are selected to analyze their quantitative impact on the imaging quality of typical imaging systems. The imaging resolution, color revent and gray scale value are selected as the main imaging parameters. The study found that the salt mist test, gas corrosion, damp heat test, high and low temperature shock, and ultraviolet test have a great impact on the optical imaging system. Long-term exposure will cause the imaging quality of the imaging system to decrease significantly, with typical parameters attenuated by more than 10%. High temperature test, low temperature test, vibration test, waterproof test, low air pressure, shock and dust test have little effect on its image quality, the system has good tolerance to it, and the typical parameter attenuation is below 5%. This paper will provide some reference for the rational use of optical imaging systems and the compilation of test standards.

For traditional imaging systems, high imaging quality and system miniaturization are often contradictory. In order to meet the requirements of high imaging quality and system miniaturization, this paper proposes a method to correct the aberration of coherent imaging optical systems. The method is based on the idea of phase recovery and the imaging principle of a coherent imaging system to recover the aberrations at the exit pupil of the system. According to the recovered aberrations, conjugate filters are constructed to correct the image quality in the frequency domain. The imaging quality of the system is improved without changing the original optical path, and the simplicity of the system is guaranteed. To solve the pupil frequency domain aberration more accurately, this paper adopts the dual competition and parallel recombination strategy based on the genetic algorithm and introduces the disaster model. The improved genetic algorithm can effectively restrain the appearance of the “precocity” phenomenon. Finally, the paraxial imaging optical path is simulated and verified by experiments. The results show that, after aberration correction, the image sharpness is improved and the edge information is richer, which verifies the feasibility of the coherent imaging system image quality enhancement method proposed in this paper.

Medical images are acquired for the purpose of gathering information regarding the disease state of a patient. The quality of the image should be a measure of how a specified task may be performed given the resulting image. Image quality is task dependent; one imaging system may provide images that allow better task performance than another system's for one task, but worse for another task. Determining the quality of an imaging system involves specifying the task of interest, the range of objects that will be imaged, and the observer (human or machine reader) who will perform the task. In radiography it has become common to use Fourier measures to describe image quality through a combination of Fourier‐based measures of system resolution and noise. The Line Spread Function, when Fourier transformed, yields the Modulation Transfer Function (MTF) as a measure of system resolution. Use of the MTF to describe a system's resolution is appropriate when the imaging system is shift‐invariant, that is, the line spread function is independent of position. Image noise is described in the Fourier domain by the Noise Power Spectrum (NPS). We can use the NPS to describe the noise in an imaging system whenever the noise properties are stationary, meaning that the variance and correlations between fluctuations in different locations are not dependent on their absolute location. These Fourier measures of system resolution and noise are commonly combined to give an overall figure of merit known as the Detective Quantum Efficiency (DQE). The DQE describes the signal‐to‐noise transfer characteristics of an imaging system as long as those assumptions of shift‐invariance and noise stationarity are valid. In digital systems the image of an object is affected by the location of the object with respect to the pixel grid. In other words, the detector pixels cause the system to be shift‐variant. In this case the MTF does not describe the resolution properties completely. This is particularly the case for tomographic systems, where the point‐response function is quite position‐dependent. Moreover, in real imaging systems the noise properties will depend on position, most notably because real patients always have structure. So, the Fourier‐domain noise concept of Noise Power Spectrum does not capture all the properties of noise for real imaging systems and tasks. In this talk we will consider a general treatment of the imaging system as a mapping of information from the patient to the data, without the assumptions inherent in Fourier analysis. We will discuss approaches to the characterization of system resolution and noise in terms of position‐dependent parameters. Once such position‐dependent imaging properties of a system are determined, we can use them to calculate measures of image quality that summarize the usefulness of the images for the performance of various visual tasks.

Sunlight background noise significantly hinders the operation of ghost imaging systems, posing a considerable challenge for target imaging under daytime sunlight conditions. This paper introduces a method to eliminate sunlight background noise using a Faraday anomalous dispersion optical filter (FADOF). A ghost imaging system based on FADOF is constructed, and experiments are conducted under strong background noise conditions. The system operates outdoors in direct sunlight, utilizing sunlight introduction system to introduce light into the detection path, directly reaching the detection end of the system. In this real sunlight noise condition, the ghost imaging system using FADOF filtering achieved nearly continuous and stable imaging throughout three summer days, contrasting with a system using a 10 nm filter that only functions properly after sunset. The research findings indicate that FADOF effectively enhances the ghost imaging system's resistance to background light noise, enabling continuous operation under conditions of strong background noise throughout the day.

Equipment requirement, quality of reconstructed image, and reconstruction time are important factors in the realization of thermal-light ghost imaging system. In this paper, we propose a new ghost imaging scheme with multiple speckle patterns, named multiple speckle patterns differential compressive ghost imaging scheme. In this scheme, the high temporal resolution requirements for detectors is reduced by continuously detecting multiple independent speckle patterns. We eliminate the background and other noises in ghost imaging system by using differential ghost imaging method. And the reconstruction time is effectively reduced simultaneously to improve the reconstructed image quality by introducing the compressive sensing techniques. Numerical results show that for the two-level grayscale “N” image, the mean square error, in using the proposed scheme with 8000 measurements, is reduced by 96.9%, and the peak signal to noise ratio has improved by 15.1 dB, in comparison with those using the original multiple speckle patterns ghost imaging scheme with 35000 measurements. For the eight-level grayscale “Pepper” image, the peak signal to noise ratio is enhanced by 11.4 dB. The proposed scheme also can decrease the requirements of detection equipment to improve the image quality, and reduce the reconstruction time. Therefore, it may have a broad application prospect.

In the ghost imaging system based on the multidimensional vector matrix Walsh transform, the Walsh speckle pattern is used to continuously sample the moving target object, so there is a certain correlation and complementary detail information between multiple frames in the ghost imaging video. In our previous research, we broke through the inherent limitations of the digital micromirror device refresh rate on ghost imaging systems, allowing us to reconstruct more detailed frames. Therefore, by utilizing the correlation between these detailed frames in the time and space domains, we can improve the comfort of ghost imaging videos from the perspective of improving the single-frame quality of ghost imaging videos. To further improve multi-frame quality by utilizing more detailed frames in ghost imaging videos, this paper proposes a ghost imaging video algorithm based on the multidimensional vector matrix Walsh transform of bidirectional N-aligned fusion frames. Combining deep learning with computational ghost imaging, utilizing a bidirectional N-alignment algorithm and a deep learning neural network framework for target frame integration. The ghost imaging videos obtained from previous research can be improved in terms of noise, motion blur, and single-frame detail richness to enhance the imaging quality of the target frame. This paper constructs an encoding module and a corresponding feature fusion module suitable for multidimensional vector Walsh transform ghost imaging from the perspective of network width and feature multi-branch extraction based on GoogleNet Inception V3. A loss function suitable for four-dimensional vector matrix Walsh transform ghost imaging has been defined, which can better eliminate the noise and distortion caused by Walsh speckle sampling. After comparing the experimental results of moving objects, the results show that the algorithm proposed in this paper has significantly improved structural similarity, blur index, noise index, and other aspects compared to existing ghost imaging video optimization methods. The similarity angle of the NRSS structure has increased by 18.58% compared to the original reconstructed image, the blur parameter has increased by 31.9%, and the noise parameter has risen by 9.22%.

Wavefront coding technique can extend the depth of filed (DOF) of the incoherent imaging system. Several rectangular separable phase masks (such as cubic type, exponential type, logarithmic type, sinusoidal type, rational type, et al) have been proposed and discussed, because they can extend the DOF up to ten times of the DOF of ordinary imaging system. But according to the research on them, researchers have pointed out that the images are damaged by the artifacts, which usually come from the non-linear phase transfer function (PTF) differences between the PTF used in the image restoration filter and the PTF related to real imaging condition. In order to alleviate the image artifacts in imaging systems with wavefront coding, an optimization model based on the PTF was proposed to make the PTF invariance with the defocus. Thereafter, an image restoration filter based on the average PTF in the designed depth of field was introduced along with the PTF-based optimization. The combination of the optimization and the image restoration proposed can alleviate the artifacts, which was confirmed by the imaging simulation of spoke target. The cubic phase mask (CPM) and exponential phase mask (EPM) were discussed as example.

The burgeoning field of astrophotonics, the interface between astronomy and photonics, is redefining astronomical instrumentation to replace traditional bulk optical systems with integrated optics. This drives the development of a new promising photonics-integrated interferometric imaging technique, called the segmented planar imaging detector for electro-optical reconnaissance (SPIDER). Compared to conventional imaging systems, SPIDER can reduce the size, weight, and power (SWaP) by one to two orders of magnitude for an equivalent imaging resolution in virtue of photonics-integrated technology. However, SPIDER has a dense lens distribution and tens of separated narrow wavebands demultiplexed by array waveguide gratings. In this paper, we developed a new simplified sparse-aperture photonics-integrated interferometer (SPIN) imaging system. The SPIN imaging system was no more a Michelson configuration interferometer as SPIDER and was designed as a Fizeau configuration interferometer imaging system. This transfer of configuration type affords a more concise structure; the SPIN was designed with much less apertures and fewer wavebands than those of SPIDER. Further, the SPIN yields enhanced modulation transfer function and imaging quality with equivalent aperture diameter, compared with SPIDER. The main barrier of this transfer is the elimination of coupling restriction at the tip of a waveguide, namely the apodization effect. This effect, which is caused by the coupling effect between Fourier lens and waveguide, hinders SPIN imaging systems from getting finer resolution. However, a microscope could be used to eliminate this effect. Moreover, a waveguide array is used to receive these finer details and enlarges the field of view in SPIN. The coupling efficiency of the waveguides and crosstalk errors between waveguides of array were analyzed, which are important for proper parameters setting in SPIN imaging system. Based on these analyses, the imaging principle was derived and a hyper-Laplacian-based imaging reconstruction algorithm was developed. A simulation of the SPIN imaging system with seven apertures and one imaging waveband demonstrated the high imaging quality.

Remote-sensing applications within atmospheric scattering environments pose substantial challenges for traditional optical imaging systems owing to photon scattering, signal attenuation, and noise-induced degradation. This paper presents a ghost imaging technique operating in the Fourier domain, integrated with adaptive multistage post-processing enhancement algorithms to improve image reconstruction fidelity in the presence of scattering media. The experimental framework utilizes a digital micromirror device (DMD) to generate structured Fourier basis patterns in the reference arm, while the signal arm traverses controllable scattering media simulated using a precision-positioned ground glass (GG) diffuser. Image reconstruction is achieved through frequency-domain correlation processing employing a three-step phase-shifting algorithm, while reconstructed image degradation is mitigated through a multi-stage enhancement pipeline incorporating adaptive denoising, deblurring, and contrast optimization algorithms. Experimental validation demonstrates that the proposed methodology achieves recognizable image reconstruction using 25% of the Fourier coefficient set under high-scattering conditions, with enhancement algorithms providing up to 30% improvement in peak signal-to-noise ratio (PSNR) relative to unprocessed reconstructions. This investigation reveals fundamental limitations in dense scattering regimes and provides insights into the computational trade-offs inherent in ghost imaging systems under challenging environmental conditions.

We show that the image quality of ghost imaging (GI) can be controlled by the use of shaped incoherent sources. The formula for the point-spread function in the GI system has been derived and is determined by the Fourier transform of the source intensity distribution. Compared with the widely used Gaussian Schell-model source, we find that using a cosine-Gaussian Schell-model source can lead to the degradation of GI quality, while the quality of GI can be increased with a cosh-Gaussian Schell-model source. Even under atmospheric turbulence, the image resolution of GI still can be improved by means of the cosh-Gaussian Schell-model source.

Quantum ghost imaging uses photon pairs produced from parametric downconversion to enable an alternative method of image acquisition. Information from either one of the photons does not yield an image, but an image can be obtained by harnessing the correlations between them. Here we present an examination of the resolution limits of such ghost imaging systems. In both conventional imaging and quantum ghost imaging the resolution of the image is limited by the point-spread function of the optics associated with the spatially resolving detector. However, whereas in conventional imaging systems the resolution is limited only by this point spread function, in ghost imaging we show that the resolution can be further degraded by reducing the strength of the spatial correlations inherent in the downconversion process.

Large depth of field (DOF) is a longstanding goal in optical imaging field. In this paper we presented a simple but efficient method to extend the DOF of a diffraction-limited imaging system using a thin scattering diffuser. The DOF characteristic of the imaging system with random phase modulation was analyzed based on the analytical model of ambiguity function as a polar display of the optical transfer function (OTF). The results of numerical simulation showed that more high-frequency components existed in the defocused OTF curve when the exit pupil of the imaging system exhibited a random phase modulation. It proved the important role of the scattering diffuser in extending the DOF of imaging systems. For the reconstruction, a stack of point spread functions (PSFs) corresponding to different axial locations within a measurement range were superimposed to construct the stacked PSF. Then the large DOF image was recovered from a speckle pattern by deconvolution. In this proof-of-concept, we experimentally demonstrated the single-shot imaging with larger DOF using a thin glass scattering diffuser in both a single-lens imaging system and a microscopic imaging system.

Two main spatial frequency and quantitative calculations and measurements am, used to study the imaging system of three industrial digital radiography (IDR) modules for non-destructive testing (NDT), namely complementary metal oxide semiconductor (CMOS) flat-panel digital detector with 50 mu m pixel pitch, computed radiography (CR) with phosphor imaging plate with 25 mu m pixel pitch and laser-type film digitiser with 50 mu m pixel pitch. The modulation transfer function (MTF) and noise power spectrum (NPS) measurement and calculations were adapted on order to evaluate the image quality of IDR images. The MTF has been used to characterise the resolution properties of analogue and digital X-ray imaging systems and measure image deterioration due to optical factors, such as diffusion of image forming radiation. The NPS is used in determining noise in images produced and the choices of normalisation of the NPS vary slightly from researcher to researcher, but the underlying methodology is consistent. In order to easily compare these two measurements and calculations, the integral of up to the system Nyquist frequency was used as the final image quality quantitative evaluation. For the MTF measurement and calculation, four regions of interest (ROI) were, defined to portray the randomness in performing real testing. The four ROI are then compared with each other. For the NPS measurement and calculation, ten ROI were defined, scattered and averaged to have overall noise estimation. From the measurements and calculations which were done, the averaged MTF at 20% modulation for the laser-type film digitiser system is 6.55 cycles/mm, CR modulated 4.48 and CMOS modulated 2.83 cycles/mm. For NPS measurement and calculation, the result obtained in decreasing order is laser-type film digitiser, CMOS and CR. The laser-type film digitiser system modulates the best transfer function at 20% but does not have the lowest NPS. The lowest and stable NPS is the CR system but it has the lowest modulating capability at 20%. The study shows that in order to perform NDT by using the evaluated modules, the user must know the true capability, of the system and how, it is designed for specific application and discontinuity detection.

Phase-coded modulation 3D ghost imaging