A system and method for identifying lithology based on images and XRF mineral inversion solving the problem that conventional lithology identification relies on manual work, which is time-consuming, subjective and can cause misjudgment. The identification system includes an autonomous vehicle; an X ray fluorescence spectrometer probe, and tests surrounding rock element information; image collection device; and vehicle-mounted processor. The processor inverts the received surrounding rock element information into mineral information based on a Barthes-Niggli standard mineral calculation method; and receive surrounding rock images and a corresponding inclination angle thereof, convert the surrounding rock images into image information in a one-dimensional vector format, splice the image and mineral information which is in a one-dimensional format, and distinguish the spliced information based on a preset neural network to identify rock lithology.

There is provided an acquiring method of a projection image of a sample whose shape is uneven with respect to a rotation center, the method comprising the steps of setting the sample S0 at a position of the rotation center C0 provided between an X-ray source 116a and a detector 117, and acquiring the projection image of the sample S0 at each different rotation angle for each different magnification ratio over a rotation angle of 180° or more by rotating the sample S0 around the rotation center C0, and by relatively changing a separation distance between the X-ray source and the rotation center, or a separation distance between the rotation center and the detector in an optical axis direction according to the shape of the sample S0 and the rotation angle of the sample S0.

A method for analyzing at least one bounded object in an electron microscope image that includes segmenting the image to provide a segmented image and measuring a dimension relative to the at least one bounded object in the segmented image. The electron microscope image can be an image of a semiconductor device that includes a pattern of bounded objects or structure of the semiconductor device.

The disclosure provides an inspection method determining whether there is a defect in an electrode structural body including a cathode electrode layer, an electrolyte layer and an anode electrode layer electrode by an image processor. The inspection method includes a step of scanning the electrode structural body along a scanning direction to obtain a continuous transmission image, a step of digitizing a shade of each pixel of the transmission image, a step of calculating a difference value between a grayscale of a specific pixel and a median value of grayscales of comparison pixels located in front or rear of the specific pixel along the scanning direction, and a step of determining presence or absence of the defect according to the difference value and a predetermined threshold value.

In an X-ray imaging apparatus, an image processor is configured to generate a super-resolved image having higher resolution in an X direction than a first fluoroscopic X-ray image and a second fluoroscopic X-ray image by dividing, in the X direction, a pixel value of a first pixel in the first fluoroscopic X-ray image based on pixel values of two pixels in the second fluoroscopic X-ray image that overlap the first pixel when the first fluoroscopic X-ray image and the second fluoroscopic X-ray image are shifted in the X direction by an amount corresponding to a movement amount (of an X-ray detection position) and displayed in an overlapping manner

The invention relates to non-destructive imaging of the internal structure for safe and intuitive operator work. In the context of the invented method, electronic scanning first creates a virtual image of the surface of the object (5) whose internal structure is the subject of research. Part of the surface of the object (5) and the angle of scanning are set by voice or by movement of the operator's body (9). The virtual image of the surface of the object (5) is subsequently projected in the stereoscopic glasses (7), followed by creation of the virtual image of the internal structure of the object (5) for the same angle of scanning. The virtual image of the internal structure is projected in the virtual image of the surface of the object (5), or replaces the virtual image of the object (5).

An X-ray single-pixel camera based on X-ray computational correlated imaging, which belongs to the technical research fields of X-ray computational correlated imaging and X-ray single-pixel imaging. The X-ray single-pixel camera includes: an X-ray modulation system (3), an X-ray modulation control system (4), an X-ray single-pixel detector (5), a main control system unit (6), a time synchronization system (7) and a computational imaging system (8). The main control system unit (6) controls each module through software; the time synchronization system (7) controls synchronization of each module for automatic collection; and the computational imaging system (8) is configured to perform a second-order correlated computation or a compressed sensing computation or a deep learning computation on the signals collected by the X-ray single-pixel detector (5) and a preset modulation matrix, so as to obtain an image of an object under test. The X-ray single-pixel camera based on X-ray computational correlated imaging, provided by the present invention, realizes single-pixel imaging, greatly reduces the sampling number while ensuring the imaging quality, and reduces the X-ray radiation dose in an imaging process.

A radiation imaging apparatus is provided. The apparatus comprises an image capturing unit that is provided with pixels for converting incident radiation into electrical signals and is configured to output first image data, a storage unit configured to store position information of a first pixel which continuously outputs an abnormal pixel value, a replacing unit configured to generate second image data from the first image data by replacing a pixel value of the first pixel with a preset setting value based on the position information and a correction unit configured to detect a second pixel which is not stored in the storage unit and outputs an abnormal pixel value, and correct the pixel value of the second pixel. The correction unit detects and corrects the second pixel based on the second image data that includes the first pixel whose pixel value has been replaced.

The present invention refers to a method of processing a EDX/XRF map (1), comprising selecting a data point (dp) among a plurality of data points of the EDX/XRF map (1), wherein each of the data points comprise a local measured value (m) and a local dispersion value (v) of a measured variable; determine a first modified mean value (M[1]) based on the local measured value (m) of the selected data point (dp) and the local measured value of at least one neighboring data point neighboring the selected data point (dp) and determine a first modified dispersion value (V[1]) based on the local dispersion value (v) of the selected data point (dp) and the dispersion value of the at least one neighboring data point, when m<th, and replace the local measured value (m) of the selected data point (dp) by the first modified mean value (M[1]), when M[1]>TH[1].

The present disclosure directs to a system and method for CT imaging. The method may include acquiring computed tomography (CT) data, wherein the CT data is generated by scanning a subject using a CT scanner, the CT scanner including a focal spot and a detector, and the detector including a plurality of detector units. The method may also include obtaining a forward projection model and a back projection model, wherein the forward projection model and the back projection model are associated with sizes of the detector units and a size of the focal spot of the CT scanner. The method may further include reconstructing a CT image of the subject iteratively based on the CT data, the forward projection model, and the back projection model.