Showing papers on "Dark-frame subtraction published in 1991"

Non-moving regions preserving median filters for image sequence filtering

Abstract: Three-dimensional weighted median filters for noise reduction in gray-level image sequences are presented. The filters are designed to retain completely nonmoving regions in image sequences. In moving regions, 3-D filter structures adapt automatically to changes in image sequence content and perform a filtering operation in moving regions. Noise attenuation capability of the filters is studied. The performance of the filters in terms of detail preservation and noise reduction is examined using real image sequences. >

The dissimilarity corner detector

Abstract: The authors present a corner detection that works by using dissimilarity along the contour direction to detect curves in the image contour. The operator is fast, robust to noise and almost self-thresholding. The standard deviation of the image noise must be specified, but this value is easily measured and the explicit modeling of image noise contributes to the robustness of the operator to noise. The authors also present a new interpretation of the Kitchen-Rosenfeld corner operator (1982) in which they show that this operator can also be viewed as the second derivative of the image function along the edge direction. >

Automated iterative noise filtering (image processing)

Abstract: An iterative method for removing signal-independent, additive noise from digital images is described. The underlying concept of this fully automated method is noise filtering by use of local statistics. Assuming that the noise is statistically stationary, noise variance is estimated from an input image by utilizing its smallest local variances. Noise filtering is performed iteratively and terminates when the estimated noise variance converges to zero. The method successfully processes degraded images by filtering noise from regions of uniform intensity while preserving texture pixels and edges. >

Apparatus and method for noise reduction of video signal dependent upon video gain

Abstract: A circuit 8 reduces noise on a video signal from an imager 6 for a TV monitor 7. The noise reduction circuit includes a video frame store connected so as to integrate the corresponding picture elements of several frames in order to reduce noise. The amount of noise reduction applied depends on the noise on the incoming video signal but, whereas this has been assessed previously by comparing differences between incoming frames, in the invention it is assessed from the gain, information on which is encoded on the video signal. The gain of the imager gives a more accurate reflection of video noise than does comparing successive frames, since movements on the image can produce the same effect as noise fluctuations.

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.

Image analysis by information decomposition and synthesis

Abstract: The authors compare the image analysis capability using the linear Gaussian pyramid and nonlinear morphological pyramid image decomposition/synthesis techniques, with emphasis on image enhancement. In the experiments, the authors used the weakening strategy of the 'between band correlation then synthesis' approach to remove two types of noise: the unstructured noise (e.g., the random sparkle noise) and the structured noise (e.g., the high-frequency imaging artifact) from an image which has been decomposed either by morphological pyramid or Gaussian pyramid techniques. White sparkle noise was successfully removed by the morphological pyramid band decomposition/synthesis approach based on an opening operation with a flat 3*3 cross structure element. In contrast, the Gaussian pyramid approach with 5*5 Gaussian kernel was not entirely successful in removing the same noise. A similar result was obtained when using both approaches for removing the structured noise. >