Quick-response (QR) code technique is combined with ghost imaging (GI) to recover original information with high quality. An image is first transformed into a QR code. Then the QR code is treated as an input image in the input plane of a ghost imaging setup. After measurements, traditional correlation algorithm of ghost imaging is utilized to reconstruct an image (QR code form) with low quality. With this low-quality image as an initial guess, a Gerchberg-Saxton-like algorithm is used to improve its contrast, which is actually a post processing. Taking advantage of high error correction capability of QR code, original information can be recovered with high quality. Compared to the previous method, our method can obtain a high-quality image with comparatively fewer measurements, which means that the time-consuming postprocessing procedure can be avoided to some extent. In addition, for conventional ghost imaging, the larger the image size is, the more measurements are needed. However, for our method, images with different sizes can be converted into QR code with the same small size by using a QR generator. Hence, for the larger-size images, the time required to recover original information with high quality will be dramatically reduced. Our method makes it easy to recover a color image in a ghost imaging setup, because it is not necessary to divide the color image into three channels and respectively recover them.
A virtually optical system with a hierarchical structure is designed for optical verification. At each hierarchical level, two phase-only masks are alternately generated using an iterative approach and then are sparsified. All sparse phase-only masks generated at the lower hierarchical levels are fixed and applied as constraints at the higher hierarchical level. Since sparse phase-only masks are applied for the decoding, the recovered images are invisible and instead can be further verified by a nonlinear correlation algorithm. The results are presented to show validity of the proposed method, and the proposed method provides a promising strategy for optical verification.
In recent years, many optical systems have been developed for securing information, and optical encryption/encoding has attracted more and more attention due to the marked advantages, such as parallel processing and multiple-dimensional characteristics. In this paper, an optical security method is presented based on pure phase encoding with biometric information. Biometric information (such as fingerprint) is employed as security keys rather than plaintext used in conventional optical security systems, and multiple-stage phase-encoding-based optical systems are designed for generating several phase-only masks with biometric information. Subsequently, the extracted phase-only masks are further used in an optical setup for encoding an input image (i.e., plaintext). Numerical simulations are conducted to illustrate the validity, and the results demonstrate that high flexibility and high security can be achieved.
This paper presents a robust iterative algorithm, known as hybrid Wirtinger flow (HWF), for phase retrieval (PR) of complex objects from noisy diffraction intensities. Numerical simulations indicate that the HWF method consistently outperforms conventional PR methods in terms of both accuracy and convergence rate in multiple phase modulations. The proposed algorithm is also more robust to low oversampling ratios, loose constraints, and noisy environments. Furthermore, compared with traditional Wirtinger flow, sample complexity is largely reduced. It is expected that the proposed HWF method will find applications in the rapidly growing coherent diffractive imaging field for high-quality image reconstruction with multiple modulations, as well as other disciplines where PR is needed.
It is well known that in ghost imaging, a large number of random phase-only masks should be applied for generating a series of reference intensity patterns. Hence, it is always concerned that data storage or transmission might be tedious in some applications. In this paper, we report how only one random phaseonly mask should be pre-generated to be stored or transmitted for ghost-imaging-based optical encryption system with sufficiently guaranteed security. During optical encoding, a method, called pixel modulation, is developed and applied to sequentially modulate this random phase-only mask. Since pixel modulation strategy possesses high invisibility and randomness, high security is guaranteed in the proposed optical system. In addition, only one random phase-only mask and sparsely binary maps are stored or transmitted as principal keys for the decoding, hence potential problem in conventional optical security systems is effectively mitigated.
Ghost imaging with single-pixel bucket detector has attracted more and more current attention due to its marked physical characteristics. However, in ghost imaging, a large number of reference intensity patterns are usually required for object reconstruction, hence many applications based on ghost imaging (such as tomography and optical security) may be tedious since heavy storage or transmission is requested. In this paper, we report that the compressed reference intensity patterns can be used for object recovery in computational ghost imaging (with single-pixel bucket detector), and object verification can be further conducted. Only a small portion (such as 2.0% pixels) of each reference intensity pattern is used for object reconstruction, and the recovered object is verified by using nonlinear correlation algorithm. Since statistical characteristic and speckle averaging property are inherent in ghost imaging, sidelobes or multiple peaks can be effectively suppressed or eliminated in the nonlinear correlation outputs when random pixel positions are selected from each reference intensity pattern. Since pixel positions can be randomly selected from each 2D reference intensity pattern (such as total measurements of 20000), a large key space and high flexibility can be generated when the proposed method is applied for authenticationbased cryptography. When compressive sensing is used to recover the object with a small number of measurements, the proposed strategy could still be feasible through further compressing the recorded data (i.e., reference intensity patterns) followed by object verification. It is expected that the proposed method not only compresses the recorded data and facilitates the storage or transmission, but also can build up novel capability (i.e., classical or quantum information verification) for ghost imaging.
Digital holography has been widely studied in recent years, and a number of applications have been demonstrated. In this paper, we demonstrate that sparsity-based phase-shifting digital holography can be applied for image authentication. In phase-shifting digital holography, the holograms are sequentially recorded. Only small parts of each hologram are available for numerical reconstruction. It is found that nonlinear correlation algorithm can be applied to simply authenticate the reconstructed object. The results illustrate that the recovered image can be correctly verified. In the developed system, the recorded holograms are highly compressed which can facilitate data storage or transmission, and one simple authentication strategy has been established instead of applying relatively complex algorithms (such as compressive sensing) to recover the object.
In this paper, we propose a method for optical image encryption based on fractional Fourier transform (FRFT) and
Arnold transform (ART) in phase-shifting digital holography. An input image is first divided into eight bit planes, and
each bit plane is encrypted based on double random-phase masks and FRFT. Complex amplitude for the object is
retrieved by phase-shifting digital holography in the hologram plane. The real and imaginary parts of the retrieved
complex amplitudes for the 0th-7th bit planes are further encrypted using ART algorithm. Numerical results are shown to
demonstrate the feasibility and effectiveness of the proposed technique. The sensitivity of security parameters, such as
function orders in FRFT and iteration number in ART method, is also analyzed.