Dark-frame subtraction

About: Dark-frame subtraction is a research topic. Over the lifetime, 1216 publications have been published within this topic receiving 20763 citations.

Characterization And Measurement Of Noise Properties For A Digital Radiography System

Abstract: An expression for the noise in digitized video images is derived assuming an arbitrary video data transformation. From this expression, the ratio of quantum noise to camera noise is detenained. Unlike the noise itself, this ratio is independent of the video data transformation. The other quantity independent of the video data transformation is the pixel contrast signal-to-noise ratio. Noise measurements for linear and logarithmic video amplification are presented and discussed. The use of noise measurements on linearly amplified video images for estimating the system signal-to-noise ratio and the noise equivalent detected photon flux is demonstrated.

Noise performance of microchannel plate imaging systems

Abstract: We present a characterization of the significant noise mechanisms in a microchannel image intensifier and CCD image recording system intended for applications in ultrafast imaging systems used at LLNL for nuclear science. The system under study consists of a generation two image intensifier a relay lens and a cooled CCD imaging array of 640 by 1024 pixels. Fixed pattern noise is significantly reduced by flat fielding techniques. The remaining major noise mechanisms are the intensifier shot noise and a noise factor that characterizes the non-idealness of the system. Results are given for the intensifier noise factor'' s functional dependence on input irradiance levels gain settings and accelerating voltages.

Imaging Filter and Noise Analyse Based on Low Intense X-ray Image System

Abstract: New structure of a low intensity Xray image system is mainly made of plane plate mode Xray intensifier of single proximity focus and CCD data acquisition and processing system. By the system composition, the paper analyses the image noise source of low Xray imaging system, and points out that the random noise is white noise which is obeyed by Poisson distribution in the whole body, yet the positivenegative interfering impulse is excited in the some locality. Then the compound methods of the "multiframe mean + extremum median filter" is submitted which deals with the imaging noise. Firstly, some frame images is superimposed, then mean image is calculated from those images, which is under the principle of noise noncorrelation. By the method, the information is enhanced and the noise is compressed. Secondly, based on the standard median filtering algorithm, the extremum median filter is ordered as much as possible to preserving the detail of the image when the noise are removed. That is to say, all the pixels are separated into signal and noise pixels according to the decision criterion given in the following; then, noise pixels are replaced with the median value of their neighborhood in the input image. The decision criterion: if a pixels value is the extremum (max or min) of its neighborhood, it is a noise pixel; else it is a signal pixel. This decision criterion is under such an assumption: inherent relationships exist among neighbor pixels. If a pixels value is far higher or lower than the others' value of its neighborhood, we may consider that it had been contaminated with noise. Else, if it is similar to the others, we consider that it represents an effective signal. By the calculation of PSNP, the methods are supper to any single method greatly. And the effect of image filter is satisfied.

Research on noise characteristics and noise depression in x-ray digital radiographic system

Abstract: In X ray digital radiographic system, there are many kinds of noises which originate from different imaging elements, such as CCD camera, scintilator photoconvertor, X ray scatter, control circuit and so on. These kinds of noises have serious influence on imaging quality. The origins and characteristics of the noises in the system are studied by means of experiments, and the method of noise depression is presented. It is shown that the results of noise depression are effective.