Defocus Noise Research Articles

CFZA camera: a high-resolution lensless imaging technique based on compound Fresnel zone aperture.

In lensless imaging using a Fresnel zone aperture (FZA), it is generally believed that the resolution is limited by the outermost ring breadth of the FZA. The limitation has the potential to be broken according to the multi-order property of binary FZAs. In this Letter, we propose to use a high-order component of the FZA as the point spread function (PSF) to develop a high-order transfer function backpropagation (HBP) algorithm to enhance the resolution. The proportion of high-order diffraction energy is low, leading to severe defocus noise in the reconstructed image. To address this issue, we propose a Compound FZA (CFZA), which merges two partial FZAs operating at different orders as the mask to strike a balance between the noise and resolution. Experimental results verify that the CFZA-based camera has a resolution that is double that of a traditional FZA-based camera with an identical outer ring breadth and can be reconstructed with high quality by a single HBP without calibration. Our method offers a cost-effective solution for achieving high-resolution imaging, expanding the potential applications of FZA-based lensless imaging in a variety of areas.

Suppressing defocus noise with U-net in optical scanning holography

Suppressing defocus noise with U-net in optical scanning holography

Deep-learning based reconstruction in optical scanning holography

Optical scanning holography (OSH) can be used to record holograms of large three-dimensional (3-D) objects, based on a two-dimensional (2-D) optical scan. For semi-transparent objects, diffraction waves from all the sections can be recorded in the hologram. Numerical reconstruction of a 3-D volumetric image from an optical scanned hologram is a difficult task. The main problems are the intensive computational load, and the heavy blurring of each reconstructed section with the defocused noise from other sections. In this paper, we propose a deep-learning network for high quality image reconstruction from the optical scanned holograms. Within the framework, a U-net structure is adopted to learn the mapping between a collection of holograms, and their reconstructed volumetric images. We use a two-pupil optical heterodyne scanning system to obtain the training data where a five-fold cross validation method is used to prevent from overfitting and produce enough images in the dataset. The deep-learning based OSH can eliminate the defocus noise and generate high quality reconstruction results from an unknown hologram. Our proposed method is significantly faster than conventional OSH reconstruction algorithms, and hence suitable for processing large holograms that are captured by OSH. The feasibility of our approach is demonstrated with numerical simulations and optical experiments. The deep-learning reconstruction method proposed in the present paper is also applicable to other digital holograms obtained from conventional digital holographic systems.

Suppressing Defocus Noise with U-Net in Optical Scanning Holography

Suppressing Defocus Noise with U-Net in Optical Scanning Holography

Holographic 3D Particle Imaging With Model-Based Deep Network

Gabor holography is an amazingly simple and effective approach for three-dimensional (3D) imaging. However, it suffers from a DC term, twin-image entanglement, and defocus noise. The conventional approach for solving this problem is either using an off-axis setup, or compressive holography. The former sacrifices simplicity, and the latter is computationally demanding and time-consuming. To cope with this problem, we propose a model-based holographic network (MB-HoloNet) for three-dimensional particle imaging. The free-space point spread function (PSF), which is essential for hologram reconstruction, is used as a prior in the MB-HoloNet. All parameters are learned in an end-to-end fashion. The physical prior makes the network efficient and stable for both localization and 3D particle size reconstructions.

Multiple-image encryption based on optical scanning holography using orthogonal compressive sensing and random phase mask

A method is proposed for multiple-image encryption based on optical scanning holography (OSH) using a random phase mask (RPM) and orthogonal compressive sensing (CS). It can destroy the linearity of the traditional OSH system and possess a superior security. On the one hand, images are preferentially preprocessed by utilizing the orthogonal CS to provide a single-layer section for OSH. Therefore, the defocus noise as well as information leakage can be controlled effectively in decryption. On the other hand, each image can be extracted separately without the others’ contents. In addition, the use of RPM can bring about a more ulterior distribution to the cyphertext, which may be better than the case without the RPM. The use of orthogonal modulation matrices and RPM can provide the additional key spaces to guarantee the security of this holography cryptosystem. Simulations and discussions are also made on the cyphertext characteristics as well as the ability of resisting occlusive attack.

New autofocus and reconstruction method based on a connected domain.

In this Letter, we propose a new method for auto-focusing and reconstruction without defocus noise in optical scanning holography. By using a connected domain (CD) to calculate the area of different domains, which are labeled by a connected component, the focus distance can be found via the smallest area of each CD. Meanwhile, the sectional images without defocus noise can also be reconstructed based on the labeled domains. The effectiveness of this method has been verified with a simulation and experiments.

Modified image fusion technique to remove defocus noise in optical scanning holography

In sectional image reconstruction based on optical scanning holography (OSH) system, tomographic images are always contaminated by defocus noise. Though lots of methods have been proposed to solve this problem, some unsatisfactory results remain. In this article, a modified image fusion method is presented based on wavelet transform and connected component algorithms to deal with the defects in a random-phase OSH system where different sectional images usually have a relative displacement, rotation and loss. The method can fully utilize redundant information and affine transformation to repair the defects, and the defocus noise can be removed well. The final sectional images are more visible.

Optical defocus noise suppressing by using a pinhole-polarizer in Fresnel incoherent correlation holography.

We propose the method that suppresses the defocus noise optically in the Fresnel incoherent correlation holographic system using a pinhole-polarizer (PP), which is made by punching a pinhole on the linear polarizer. The system configuration of this suggestion is based on the original system with optical-sectioning capability, which is realized by presenting the phase-pinhole on the phase-only spatial light modulator. In our system, the phase-pinhole is replaced with a PP. The replaced component is no longer programmable yet provides an affordable, simple, and light-efficient system configuration. The feasibility of the system with the PP is analyzed and demonstrated.

Analysis of the noise in backprojection light field acquisition and its optimization.

Light field reconstruction from images captured by focal plane sweeping can achieve high lateral resolution comparable to the modern camera sensor. This is impossible for the conventional micro-lenslet-based light field capture systems. However, the severe defocus noise and the low depth resolution limit its applications. In this paper, we analyze the defocus noise in the focal-plane-sweeping-based light field reconstruction technique, and propose a method to reduce the defocus noise. Both numerical and experimental results verify the proposed method.

Potential role for microfluctuations as a temporal directional cue to accommodation.

The goal was to revisit an important, yet unproven notion that accommodative microfluctuations facilitate the determination of direction (sign) of abrupt focus changes in the stimulus to accommodation. We contaminated the potential temporal cues from natural accommodative microfluctuations by presenting uncorrelated external (screen) temporal defocus noise that combined with the retinal image effects of natural microfluctuations. A polychromatic Maltese spoke pattern thus either modulated defocus at a combination of two temporal frequencies (on-screen noise condition) or was static (control condition). The on-screen conditions were combined with step changes in optical vergence that were randomized in direction and magnitude. Five subjects monocularly viewed stimuli through a Badal optical system in a Maxwellian view. An artificial 4-mm aperture was imaged at the entrance pupil of the eye. Wavefront aberrations were measured dynamically at 50 Hz using a custom Shack–Hartmann aberrometer. Dynamic changes in the Zernike defocus term with step changes in optical vergence were analyzed. We calculated the percentage of correct directional responses for 1, 2, and 3 D accommodative and disaccommodative step stimuli using preset criteria for latency, velocity, and persistence of the response. The on-screen noise condition reduced the percent-correct responses compared to the static stimulus, suggesting that this manipulation affected the detectability of the sign of the accommodative stimulus. Several possible reasons and implications of this result are discussed.

Extended focused imaging and depth map reconstruction in optical scanning holography.

In conventional microscopy, specimens lying within the depth of field are clearly recorded whereas other parts are blurry. Although digital holographic microscopy allows post-processing on holograms to reconstruct multifocus images, it suffers from defocus noise as a traditional microscope in numerical reconstruction. In this paper, we demonstrate a method that can achieve extended focused imaging (EFI) and reconstruct a depth map (DM) of three-dimensional (3D) objects. We first use a depth-from-focus algorithm to create a DM for each pixel based on entropy minimization. Then we show how to achieve EFI of the whole 3D scene computationally. Simulation and experimental results involving objects with multiple axial sections are presented to validate the proposed approach.

Defocus noise suppression with combined frame difference and connected component methods in optical scanning holography.

Random phase masks can transform the defocus noise into a speckle-like pattern in optical scanning holography (OSH). In this Letter, we presented a speckle reduction based on combined frame difference and connected component method in a random phase-coded OSH system. The image quality of the reconstructed sections is improved with better visibility.

Effect of SNR Estimation in Defocus Blurred Image Restoration

A blind image restoration method is proposed to improve the quality of the image blurred by camera defocus and system noise. Firstly, the focus point spread function (PSF) of the blurred image is estimated through error-parameter analysis method. Secondly, the Signal-to-Noise Ratio (SNR) of the blurred image is estimated through local deviation method. Thirdly, utilizing the estimated defocus PSF and SNR, image restoration is performed through Wiener filtering method, in which circulation boundary method is adopted to reduce ringing effect. Experimental results show that the SNR of the blurred image is estimated approximately, and verify the great effect of SNR estimation in blind image restoration.

Solving inverse problems for optical scanning holography using an adaptively iterative shrinkage-thresholding algorithm

Optical scanning holography (OSH) records a three-dimensional object into a two-dimensional hologram through two-dimensional optical scanning. The recovery of sectional images from the hologram, termed as an inverse problem, has been previously implemented by conventional methods as well as the use of l₂ norm. However, conventional methods require time consuming processing of section by section without eliminating the defocus noise and the l₂ norm method often suffers from the drawback of over-smoothing. Moreover, these methods require the whole hologram data (real and imaginary parts) to eliminate the twin image noise, whose computation complexity and the sophisticated post-processing are far from desirable. To handle these difficulties, an adaptively iterative shrinkage-thresholding (AIST) algorithm, characterized by fast computation and adaptive iteration, is proposed in this paper. Using only a half hologram data, the proposed method obtained satisfied on-axis reconstruction free of twin image noise. The experiments of multi-planar reconstruction and improvement of depth of focus further validate the feasibility and flexibility of our proposed AIST algorithm.

Blind sectional image reconstruction for optical scanning holography

Optical scanning holography is a powerful holographic recording technique in which only a single two-dimensional scan is needed to record three-dimensional information. As in standard digital holography, for the reconstruction of a sectional image, the resulting data must then be postprocessed to obtain sectional content. We propose a blind sectional image reconstruction technique to automate the data processing. This reconstruction uses edge information to determine the appropriate Fresnel zone plates automatically and applies inverse imaging to recover the sectional images with significant suppression of the defocus noise. The experimental data used to verify the algorithm are measured from a physical implementation of the optical scanning holography system.

Reconstruction of sectional images in holography using inverse imaging

This paper discusses the reconstruction of sectional images from a hologram generated by optical scanning holography. We present a mathematical model for the holographic image capture, which facilitates the use of inverse imaging techniques to recover individual sections. This framework is much more flexible than existing work, in the sense that it can handle objects with multiple sections, and possibly corrupted with white Gaussian noise. Simulation results show that the algorithm is capable of recovering a prescribed section while suppressing the other ones as defocus noise. The proposed algorithm is applicable to on-axis holograms acquired by conventional holography as well as phase-shifting holography.

Sub-pixel detection of a grid's node positions for optical diagnostics

A methodology of the detection of a grid's node positions with sub-pixel accuracy is described. The algorithm uses a correlation method for locating the nodes, determines the neighbourhood relations, then calculates the node positions with sub-pixel accuracy either by locating the local maxima of the correlation function either by centroiding or fitting. The accuracy of the algorithm is studied as a function of grid geometry, grid distortion, grid defocus and image noise using synthetic images, and optimum parameters are determined.

Optical sectioning by optical scanning holography and a Wiener filter

I propose a novel digital technique that reduces defocus noise in the reconstruction of the sectional images from the complex hologram of a thick object. In three-dimensional microscopy applications of holography, reducing the defocused light scattered from outside the focused plane is an important issue. In this technique I first extract a complex hologram of a thick object by using optical scanning holography. After that, I separate the power spectra of the focused and defocused planes from the complex hologram. Finally, I construct a Wiener filter by use of the power spectra. The Wiener filter reduces the defocus noise in the reconstruction of the sectional image of the focused plane. Computer simulations show that the proposed Wiener filter reduces the defocus noise and provides the sectional images.