Optical encryption is an actively developing field of science. The majority of encryption techniques use coherent illumination and suffer from speckle noise, which severely limits their applicability. The spatially incoherent encryption technique does not have this drawback, but its effectiveness is dependent on the Fourier spectrum properties of the image to be encrypted. The application of a quick response (QR) code in the capacity of a data container solves this problem, and the embedded error correction code also enables errorless decryption. The optical encryption of digital information in the form of QR codes using spatially incoherent illumination was implemented experimentally. The encryption is based on the optical convolution of the image to be encrypted with the kinoform point spread function, which serves as an encryption key. Two liquid crystal spatial light modulators were used in the experimental setup for the QR code and the kinoform imaging, respectively. The quality of the encryption and decryption was analyzed in relation to the QR code size. Decryption was conducted digitally. The successful decryption of encrypted QR codes of up to 129 × 129 pixels was demonstrated. A comparison with the coherent QR code encryption technique showed that the proposed technique has a signal-to-noise ratio that is at least two times higher.

The method of measurement of imaging sensors noise by automatic segmentation of nonuniform targets is analyzed. Modifications to this method, which allows one to obtain unbiased estimation of temporal noise, calculation speed boost and separate measurement of dark and light temporal noises, are proposed. Merely two frames can be used for noise measurement with the modified method. Temporal noise measurement error of the modified method was analytically derived and experimentally verified. Light and dark temporal noises of consumer, video-surveillance, and industrial and scientific cameras were measured using the modified method.

High-speed optical reconstruction of 3D-scenes can be achieved using digital holography with binary digital micromirror devices (DMD) or a ferroelectric spatial light modulator (fSLM). There are many algorithms for binarizing digital holograms. The most common are methods based on global and local thresholding and error diffusion techniques. In addition, hologram binarization is used in optical encryption, data compression, beam shaping, 3D-displays, nanofabrication, materials characterization, etc. This paper proposes an adaptive binarization method based on a combination of local threshold processing, hologram division into blocks, and error diffusion procedure (the LDE method). The method is applied for binarization of optically recorded and computer-generated digital holograms of flat objects and three-dimensional scenes. The quality of reconstructed images was compared with different methods of error diffusion and thresholding. Image reconstruction quality was up to 22% higher by various metrics than that one for standard binarization methods. The optical hologram reconstruction using DMD confirms the results of the numerical simulations.

Speed up of transmission of information about 3D-scenes and reducing of archival memory size required to store it, are important for surveillance systems and biomedical applications. For solution of these tasks, methods of digital hologram compression are used. In the paper the most popular methods are considered. They can be divided into three groups: methods based on images and video compression standards, scalar methods and vector methods. Advantages and drawbacks of the methods are considered

Hybrid optical-digital systems based on diffractive correlator are being actively developed. To correctly estimate application capabilities of cameras of different types in optical-digital correlation systems knowledge of modulation transfer function (MTF) and light depended temporal and spatial noises is required. The method for measurement of 2D MTF is presented. The method based on random target method but instead of a random target the specially created target with flat power spectrum is used. It allows to measure MTF without averaging 1D Fourier spectra over rows or columns as is in the random target method and to achieve all values of 2D MTF instead of just two orthogonal cross-sections. The simple method for measuring the dependence of camera temporal noise on light signal value by shooting a single scene is described. Measurements results of light and dark spatial and temporal noises of cameras are presented. Procedure for obtaining camera's light spatial noise portrait (array of PRNU values for all photo sensor pixels) is presented. Results on measurements of MTF and temporal and spatial noises for consumer photo camera, machine vision camera and videosurveillance camera are presented.