Abstract: Digital detectors of X-ray image intended for stitching and linearization of gain characteristics of independent sensors of multisensor detectors are disclosed. The technical result is the development of methodology of stitching and linearization of multisensor detectors gain characteristics under the conditions of non equal irradiance (the use of radiation source with flat X-ray (light) field is not required). The method is based on calculation of LUT functions for conversion of output signals intensity of detector sensors. As a result of application of the stated conversion LUT functions the sensors gain characteristics are received which are the same and linear within the precision of measurements. Calculation of stitching LUT functions employs the availability of non-equal X-ray (light) field slowly changing along the area of detector. The responses of any two adjacent sensors with the same gain characteristics shall have similar values near the joint of these sensors.

Abstract: Digital detectors of X-ray image intended for stitching and linearization of gain characteristics of independent sensors of multisensor detectors are disclosed. The technical result is the development of methodology of stitching and linearization of multisensor detectors gain characteristics under the conditions of non equal irradiance (the use of radiation source with flat X-ray (light) field is not required). The method is based on calculation of LUT functions for conversion of output signals intensity of detector sensors. As a result of application of the stated conversion LUT functions the sensors gain characteristics are received which are the same and linear within the precision of measurements. Calculation of stitching LUT functions employs the availability of non-equal X-ray (light) field slowly changing along the area of detector. The responses of any two adjacent sensors with the same gain characteristics shall have similar values near the joint of these sensors.

Abstract: The method includes acquisition of an original image; low-frequency filtering of the original image to obtain an estimated image; a noise image development as a difference between the original and estimated images by morphologic filtering elimination of noise image pixels corresponding to sharp changes in the original image; dividing an intensity range of the estimated image into intervals, wherein each pixel of the estimated image relates to an appropriate interval; accumulating some noise image pixels corresponding to estimated image pixels; calculating interval estimations of noise dispersion using accumulated noise image pixels; improving interval estimations by removing noise pixels according to ? 3 criteria, approximating interval estimations of noise dispersion resulting in tabular function of noise vs.