RESUMEN
Single-pixel imaging could be a superior solution for imaging applications where the detector array is very expensive or not even available. Sampling order, sampling ratio, noise and type of transforms affect the quality of the reconstructed image. Here, we compare the performance of single pixel imaging (SPI) with Hadamard transform (HT) and discrete cosine transform (DCT) in the presence of noise. The trade-off between adding image information and adding noise in each coefficient measurement results in an optimum number of measurements for reconstruction image quality. In addition, DCT shows higher image quality with fewer measurements than HT does. We then demonstrate our SPI with optimum sampling strategy for a large set of images and lab experiments and finally put forward a quality control technique, which is corroborated by the practical experiments. Our results suggest a practical approach for SPI to improve the speed and achieve the highest possible image quality.
RESUMEN
Benefiting from the memory effect (ME) for speckle intensity correlations, only one single-shot speckle pattern can be used for the high-quality recovery of objects. However, ME gives a restriction to the field of view (FOV) for imaging with scattering media. Objects beyond the ME region cannot be recovered and produce unwanted speckle patterns, which cause reduction in the speckle contrast and recovery quality. Nevertheless, all the spatial information from a large object is embedded in a single speckle image. Here, we extract the spatial information from these unavoidable speckle patterns and enlarge the FOV of the imaging system with scattering media. Regional point spreading functions, which are fixed and only need to be recorded once for all-time use, are employed to recover corresponding spatial regions of an object by deconvolution. Then, an automatic weighted averaging in an iterative process is performed to obtain the object with significantly enlarged FOV. Our results present an important advancement of imaging techniques with strongly scattering media.
RESUMEN
A position-multiplexing technique with ultra-broadband illumination is proposed to enhance the information security of an incoherent optical cryptosystem. This simplified optical encryption system only contains one diffuser acting as the random phase mask (RPM). Incoherent light coming from a plaintext passes through this nature RPM and generates the corresponding ciphertext on a camera. The proposed system effectively reduces problems of critical alignment sensitivity and coherent noise that are found in the coherent illumination. Here, the use of ultra-broadband illumination has the advantage of reducing the speckle contrast that makes the ciphertext more complex. Reduction of the ciphertext size further increases the strength of the ciphering. Using the spatial decorrelation of the speckle pattern we have demonstrated a position multiplexed based cryptosystem, where the ciphertext is the superposition of uniquely encrypted texts from various spatial positions. These unique spatial keys are utilized to decrypt the plaintext located at different spatial positions, and a complete decrypted text can be concatenated with high fidelity. Benefiting from position-multiplexing, the information of interest is scrambled together by a truly random method in a smaller ciphertext. A high performance security for an optical cryptosystem has been achieved in a simple setup with a ground glass diffuser as a nature RPM, the broadband incoherent illumination and small position-multiplexed ciphertext.
RESUMEN
Atrial fibrillation (A-fib) is the most common cardiac arrhythmia. To effectively treat or prevent A-fib, automatic A-fib detection based on Electrocardiograph (ECG) monitoring is highly desirable. This paper reviews recently developed techniques for A-fib detection based on non-episodic surface ECG monitoring data. A-fib detection methods in the literature can be mainly classified into three categories: (1) time domain methods; (2) frequency domain methods; and (3) non-linear methods. In general the performances of these methods were evaluated in terms of sensitivity, specificity and overall detection accuracy on the datasets from the Physionet repository. Based on our survey, we conclude that no promising A-fib detection method that performs consistently well across various scenarios has been proposed yet.