Персона: Козлов, Александр Валерьевич
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An optical-digital method of noise suppression in digital holography
Interpolation-Filtering Method for Image Improvement in Digital Holography
Digital holography is actively used for the characterization of objects and 3D-scenes, tracking changes in medium parameters, 3D shape reconstruction, detection of micro-object positions, etc. To obtain high-quality images of objects, it is often necessary to register a set of holograms or to select a noise suppression method for specific experimental conditions. In this paper, we propose a method to improve filtering in digital holography. The method requires a single hologram only. It utilizes interpolation upscaling of the reconstructed image size, filtering (e.g., median, BM3D, or NLM), and interpolation to the original image size. The method is validated on computer-generated and experimentally registered digital holograms. Interpolation methods coefficients and filter parameters were analyzed. The quality is improved in comparison with digital image filtering up to 1.4 times in speckle contrast on the registered holograms and up to 17% and 29% in SSIM and NSTD values on the computer-generated holograms. The proposed method is convenient in practice since its realization requires small changes of standard filters, improving the quality of the reconstructed image.
Improving the reliability of digital camera identification by optimizing the algorithm for comparing noise signatures
Virtual camera-based analysis of photosensor characterization methods
A method for measuring digital camera noise by automatic segmentation of a striped target
Currently, cameras are widely used in scientific, industrial and amateur tasks. Thus, one needs to be able to quickly evaluate characteristics and capabilities of a particular camera. A method for measuring noise components of the camera photosensor is proposed. It allows one to estimate shot noise, dark temporal noise, photo response non-uniformity and dark signal non-uniformity. For noise measurement, just two images of the same scene need to be registered. The scene consists of several stripes (quasihomogeneous regions). Then the images are processed by automatic signal segmentation. The performance and accuracy of the proposed method are higher than or equal to other fast methods. The experimental results obtained are similar to those derived using a time-consuming standard method within a measurement error.
Estimation of the Efficiency of Digital Camera Photosensor Noise Measurement Through the Automatic Segmentation of Non-Uniform Target Methods and the Standard EMVA 1288
This paper discusses the problem of characterizing digital cameras and the determination of their noise characteristics, which is relevant for contemporary photographic equipment. The issues of limiting the accuracy of data obtained with digital cameras, related to the photosensor noise, are also highlighted. The European Machine Vision Association standard EMVA 1288 for measurement and presentation of specifications for machine vision sensors and cameras, and fast automatic segmentation of non-uniform target (ASNT) noise estimation methods are compared. The noise characteristics of the photosensors of the machine vision camera PixeLink PL-B781F, scientific camera Retiga R6, and amateur camera Canon EOS M100 are investigated. The accuracies of the measurement results and speed of calculation and the method implementation are also analyzed. The assessment of the temporal noise revealed that the ASNT method is not inferior in terms of accuracy compared to the standard method and can be implemented significantly faster, even with additional images taken into account for accuracy improvement.