Single pixel imaging based on semi-continuous wavelet transform

Single pixel imaging is a novel imaging technique,and it becomes a focus of research in recent years due to its advantages such as high lateral resolution and high robustness to noise.Imaging speed is one of the critical shortcomings,which limits the further development and applications of this technique.In this paper,we focus on the issues of imaging efficiency of a single pixel imaging system.We propose semi-continuous wavelet transform(SCWT)protocol and introduce the protocol into the single pixel imaging system.The proposed protocol is something between continuous wavelet transform and discrete wavelet transform,which allows the usage of those smooth(usually non-orthogonal,and they have advantages in representing smooth signals compressively,which can improve the imaging speed of single pixel imaging)wavelets and with limited numbers of measurements.The proposed imaging scheme is studied,and verified by simulations and experiments.Furthermore,a comparison between our proposed scheme and existing imaging schemes are given.According to the results,the proposed SCWT scheme is proved to be effective in reconstructing a image compressively.

Hyperspectral Imaging Based on Compressive Sensing: Determining Cancer Margins in Human Pancreatic Tissue <i>ex Vivo</i>, a Pilot Study

Cancer is the second-leading cause of death in the United State and surgery remains the primary treatment for most solid mass tumors. However, accurately identifying tumor margins in real-time remains a challenge. In this study, the design and testing of hyperspectral imaging (HSI) system based on a single-pixel camera engine is discussed. The primary advantage of a single pixel architecture over traditional scanning HSI techniques is its high sensitivity and potential to function at low light levels. The objective for the imaging system described here is to detect changes in the reflectance spectra of tissue and to use these differences to delineate tumor margins. This paper presents the results of a 19-patient pilot study that assesses the ability of the HSI system to use reflectance imaging to delineate adenocarcinoma tumor margins in human pancreatic tissue imaged ex vivo. Pancreatic tissue excised during pancreatectomy was imaged immediately after being sent to the pathology lab. A pathologist sectioned the tissue and placed samples into standard tissue embedding cassettes. These tissue samples were then imaged using the HSI system. After imaging, the samples were returned to the pathologist for processing and analysis. The HSI was later compared to the histological analysis. The spectral angle mapping (SAM) and support vector machine (SVM) algorithms were used to classify pixels in the HSI images as healthy or unhealthy in order to delineate margins. Good agreement between margins determined via HSI (using both SAM and SVM) and histology/white light imaging was found.

Single Photon Compressive Imaging Based on Digital Grayscale Modulation Method

In single-pixel imaging or computational ghost imaging,the measurement matrix has a great impact on the performance of the imaging system,because it involves modulation of the optical signal and image reconstruction.The measurement matrix reported in the existing literatures is first binarized and then loaded onto the digital micro-mirror device(DMD)for optical modulation,that is,each pixel can only be modulated into on-off states.In this paper,we propose a digital grayscale modulation method for more efficient compressive sampling.On the basis of this,we demonstrate a single photon compressive imaging system.A control and counting circuit,based on field-programmable gate array(FPGA),is developed to control DMD to conduct digital grayscale modulation and count single-photon pulse output from the photomultiplier tube(PMT)simultaneously.The experimental results show that the imaging reconstruction quality can be improved by increasing the sparsity ratio properly and compressive sampling ratio(SR)of these gray-scale matrices.However,when the compressive SR and sparsity ratio are increased appropriately to a certain value,the reconstruction quality is usually saturated,and the imaging reconstruction quality of the digital grayscale modulation is better than that of binary modulation.

Full-waveform fast correction method for photon counting Lidar

The first photon bias of photon detection results in distortion of the photon waveform,which seriously affects the accurate acquisition of target information.A rapid universal recursive correction method is proposed,which is suitable for multi-trigger and single-trigger modes of photon detection.The calculation time is 2 to 3 orders of magnitude faster than that of Xu et al.'s method.In the experiment,we have obtained good correction results for area targets and targets with varying depths.When the average number of echo photons is 0.89,the correlation distance of the correction waveform is reduced by 85%.