Efficient and accurate conversion-gain estimation of a photon-counting image sensor based on the maximum likelihood estimation.

We establish a method for estimating conversion gains of image sensors on the basis of a maximum likelihood estimation, one of the most common and well-established statistical approaches. A numerical simulation indicates the proposed method can evaluate the conversion gain more accurately with less data accumulation than known approaches. We also applied this method to experimental images accumulated under a photon-counting-regime illumination condition by a CMOS image sensor that can distinguish how many photoelectrons are generated in each pixel. Resultantly, the conversion gains were determined with an accuracy of three digits from 1000 observed images, whose number is at most 10 times smaller than that required for achieving a similar accuracy by known gain-estimation methods.

Laboratory-size x-ray microscope using Wolter mirror optics and an electron-impact x-ray source.

We developed a laboratory-size three-dimensional water-window x-ray microscope using condenser and objective grazing incidence Wolter type I mirrors, an electron-impact-type x-ray source, and a back-illuminated CCD. The imaging system was improved for practical applications in life science research fields. Using a new objective mirror with reduced figure errors, a resolution limit of 3.1 line pairs/µm was achieved for two-dimensional transmission images and sub-micrometer-scale three-dimensional structures were resolved. Incorporating a cryogenic stage into the x-ray microscope, we observed biological samples embedded in ice to evaluate the usefulness of observation in the water-window region and multi-energy observation was demonstrated using an x-ray source with multiple x-ray tubes.

Photon-counting 3D integral imaging with less than a single photon per pixel on average using a statistical model of the EM-CCD camera.

We investigate photon-counting 3D integral imaging (PCII) with an electron multiplying charged-coupled device (EM-CCD) camera using dedicated statistical models. Using conventional integral imaging reconstruction methods with this camera in photon-counting conditions may result in degraded reconstructed image quality if multiple photons are detected simultaneously in a given pixel. We propose an estimation method derived from the photon detection statistical model of the EM-CCD to address the problems caused by multiple photons detected at the same pixel and provide improved 3D reconstructions. We also present a simplified version of this statistical method that can be used under the correct conditions. The imaging performance of these methods is evaluated on experimental data by the peak signal-to-noise ratio and the structural similarity index measure. The experiments demonstrate that 3D integral imaging substantially outperforms 2D imaging in degraded conditions. Furthermore, we achieve imaging in photon-counting conditions where, on average, less than a single photon per pixel is detected by the camera. To the best of our knowledge, this is the first report of PCII with the EM-CCD camera employing its statistical model in 3D reconstruction of PCII.

Three-dimensional integral imaging in photon-starved environments with high-sensitivity image sensors.

Imaging in poorly illuminated environments using three-dimensional (3D) imaging with passive imaging sensors that operate in the visible spectrum is a formidable task due to the low number of photons detected. 3D integral imaging, which integrates multiple two-dimensional perspectives, is expected to perform well in the presence of noise, as well as statistical fluctuation in the detected number of photons. In this paper, we present an investigation of 3D integral imaging in low-light-level conditions, where as low as a few photons and as high as several tens of photons are detected on average per pixel. In the experimental verification, we use an electron multiplying charge-coupled device (EM-CCD) and a scientific complementary metal-oxide-semiconductor (sCMOS) camera. For the EM-CCD, a theoretical model for the probability distribution of the pixel values is derived, then fitted with the experimental data to determine the camera parameters. Likewise, pixelwise calibration is performed on the sCMOS to determine the camera parameters for further analysis. Theoretical derivation of the expected signal-to-noise-ratio is provided for each image sensor and corroborated by the experimental findings. Further comparison between the cameras includes analysis of the contrast-to-noise ratio (CNR) as well as the perception-based image quality estimator (PIQE). Improvement of image quality metrics in the 3D reconstructed images is successfully confirmed compared with those of the 2D images. To the best of our knowledge, this is the first experimental report of low-light-level 3D integral imaging with as little as a few photons detected per pixel on average to improve scene visualization including occlusion removal from the scene.