Showing papers on "Dark-frame subtraction published in 1992"
23 Mar 1992
TL;DR: A scheme for noise reduction of image sequences by adaptively switching, on a block-by-block basis, between simple (nondisplaced) frame averaging and motion-compensated frame averaging is represented.
Abstract: A scheme for noise reduction of image sequences by adaptively switching, on a block-by-block basis, between simple (nondisplaced) frame averaging and motion-compensated frame averaging is represented. The resulting noise reduction approaches that achievable with simple frame averaging, while maintaining the good image resolution achievable for motion compensated frame averaging. >
96 citations
Patent•
30 Dec 1992
TL;DR: In this paper, a method and apparatus for reducing noise and enhancing the dynamic range of an image data set gather from an array of transducers (T) is described, which includes the step of processing the image data sets in a digital computer (17) by a noise reduction technique, such as deconvolving the noise component by means of a CLEAN or other algorithm.
Abstract: A method and apparatus for reducing noise and enhancing the dynamic range of an image data set gather from an array (12) of transducers (T). The method includes the step of processing the image data set in a digital computer (17) by a noise reduction technique, such as deconvolving the noise component by means of a CLEAN or other algorithm. Thereafter the artifact image data introduced by the noise reduction technique is reduced by masking the processed image data set with the original image data set. This masking is done by multiplying each data value in the processed image data set by the corresponding data value in the original image data set. The method further includes scaling and normalizing the masked data and finally displaying the same on an image display device (42). Additionally, for imaging apparatus (10) not having a cross-correlator (16), phase aberration is reduced by performing a coordinate transformation step prior to noise reduction using a non-standard set of coordinate transformation algorithms.
48 citations
TL;DR: Two statistical methods, the Moran test and the join-count statistic, are used to examine the noise parts of digital images and show that most digital images contain only 8-9 bits of correlated information.
Abstract: It is assumed that the data bits of a pixel in digital images can be divided into signal and noise bits. The signal bits occupy the most significant part of the pixel and the noise bits the least significant part. The signal part of each pixel are correlated while the noise parts are uncorrelated. Two statistical methods, the Moran test and the join-count statistic, are used to examine the noise parts. Images from three digital modalities-computerized tomography, magnetic resonance and computed radiography-are used for the evaluation of the noise bits. A residual image is formed by subtracting the original image from its smoothed version. The noise level in the residual image is then identical to that in the original image. Both statistical tests are then performed on the bit planes of the residual image. The results show that most digital images contain only 8-9 bits of correlated information.
42 citations
30 Aug 1992
TL;DR: This contribution describes the work-in-progress about MTF restoration with reduced noise enhancement, where the purpose of this type of image processing is to facilitate the observer tasks in manipulating small catheter tips in a noisy image.
Abstract: In digital diagnostic X-ray imaging the lowpass filtering of the image scene by the system MTF often has to be compensated. Edge enhancement techniques are widely applied, however, in fluoroscopy, where the images are quantum limited, the noise is also enhanced Classical edge enhancement techniques introduce correlated noise structures. These dynamic artefacts deteriorate the conspicuity of fine detail. This contribution describes the work-in-progress about MTF restoration with reduced noise enhancement. As the purpose of this type of image processing is to facilitate the observer tasks in manipulating small catheter tips in a noisy image, the final judgement belongs to this specialized group of experienced observers. The technical comparison, however, has to provide measures such as MTF enhancement, correlation between pixels, signal-to-noise ratios. >
16 citations
Patent•
15 Sep 1992
TL;DR: In this paper, a method for identifying and removing noise from digitized images includes the steps for judging whether or not a group of black pixels represents a noise by analyzing the number of pixels in the group, the degree of flattening of the group and the curvature of the region.
Abstract: A method for identifying and removing noise from digitized images includes the steps for judging whether or not a group of black pixels represents a noise by analyzing the number of pixels in the group, the degree of flattening of the group and the curvature of the region. According to the inventive method, since the entire region is scanned at once, allowing the detection of various sized pixel groups, the black pixel groups meeting a predetermined level can be selected and removed from a corresponding predefined region. Thus, noise can be removed from several predefined regions using a different noise level for each region.
12 citations
01 Nov 1992
TL;DR: There is a need to reduce the noise by pre-processing the SHD image, so as to maintain image quality and improve the encoding process, by applying adaptive noise removal techniques to the perceptually transparent and very high quality coding of still SHD images.
Abstract: The encoding of Super High Definition Images presents new problems with regard to the effect of noise on the quality of images and on coding performance. Although the information content of images decreases with increasing resolution, the noise introduced in the image acquisition or scanning process, remains at a high level, independently of resolution. Although this noise may not be perceptible in the original image, it will effect the quality of the encoded image, if the encoding process introduces correlation and structure in the coded noise. Further, the coder performance will be affected by the noise, even if the noise is not perceived. Therefore, there is a need to reduce the noise by pre-processing the SHD image, so as to maintain image quality and improve the encoding process. The reduction of noise cannot be performed by low pass filtering operations that will degrade image quality. We are applying to this problem image analysis for adaptive noise removal. We discuss first the information theoretic issues on the effect of noise on coders. We then consider adaptive noise removal techniques to the perceptually transparent and very high quality coding of still SHD images.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
8 citations
01 Oct 1992
TL;DR: This work considered the realistic case of a non-stationary image model and signal dependent noise of photonic and film-grain origins and the Baysian filter was found to outperform the adaptive Wiener filter.
Abstract: We have developed and implemented two locally adaptive image restoration filters to improve the signal to noise ratio of mammographic images. Previous efforts in restoration of digitized mammograms have assumed a stationary image with uncorrelated noise. In this work we considered the realistic case of a non-stationary image model and signal dependent noise of photonic and film-grain origins. The Baysian filter was found to outperform the adaptive Wiener filter. Both filters were implemented in real time as part of our mammographic image acquisition and analysis system.
8 citations
Patent•
02 Jun 1992TL;DR: In this paper, the noise characteristic in which has no vertical correlation and of which frequency component has 2 MHz or more in a horizontal direction at least is used to reduce the impulse noise component.
Abstract: An image signal processing system such as a television, a video tape recorder, a video disk player, a digital camera and the like, more particularly to an impulse noise reduction method and circuit which can reduce impulse noise component effectively in the image signal without damage of the original input image signal by using the noise characteristic in which has no vertical correlation and of which frequency component has 2 MHz or more in a horizontal direction at least.
8 citations
Patent•
06 Mar 1992TL;DR: In this paper, a circuit for eliminating a ghost noise of an image processing system in transmitting an image signal was proposed, wherein an image data and a noise are separated from each other visually and the ghost noise added during transmitting is changed to a white noise so as to reduce an extent of deterioration of a picture quality.
Abstract: A circuit for eliminating a ghost noise of an image processing system in transmitting an image signal, wherein an image data and a noise are separated from each other visually and the ghost noise added during transmitting is changed to a white noise so as to reduce an extent of deterioration of a picture quality because a pattern of a data scrambled at each frame is changed by an initial value being different at each frame.
6 citations
Patent•
17 Sep 1992
TL;DR: In this paper, instead of judging a noise only from an objective pixel and its neighboring pixels, the method judges whether or not a group of black pixels (including isolated points) is a noise from the number of pixels of the group, flattening and curvature, and that it can erase a noise of basically plural pixels.
Abstract: This invention method is characterized in that, instead of judging a noise only from an objective pixel and its neighboring pixels, the method judges whether or not a group of black pixels (including isolated points) is a noise from the number of pixels of the group, flattening and curvature, and that it can erase a noise of basically plural pixels. Since this invention method scans all the regions once, detects all the black pixel groups of the different size from small to large, and selects and takes out the black pixel groups meeting predetermined levels after detection, noise levels may easily be changed in parts. Since the size and shape may be designated in addition to a pixel, this invention method is highly effective for printing.
3 citations
26 Jun 1992
TL;DR: The effects of detector size and shape in the imaging properties of confocal microscopes are discussed in this article, where the authors consider the effect of various parameters on the performance of extended focus and autofocus algorithms.
Abstract: The effects of detector size and shape in the imaging properties of confocal microscopes are discussed The presence of stray light in the optical system, shot noise on the beam and detector performance limit the signal to noise ratio available The effects on the noise performance of the extended-focus (mean) and autofocus (peak) algorithms for forming image projections are presented Consideration of these various parameters allows the microscope user to obtain the best performance from his instrument for particular applications© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering Downloading of the abstract is permitted for personal use only
18 May 1992
TL;DR: In this article, a filtering method for precision tracking of the centroid of a target from a FLIR imaging sensor is presented, and statistical characterization of centroid and offset between two consecutive frames of the target is derived.
Abstract: A filtering method for precision tracking of the centroid of a target from a FLIR imaging sensor is presented. Statistical characterization of the centroid and the centroid offset between two consecutive frames of the target is derived. The relations that map the video noise statistics into the measurement noise statistics are analyzed, and their explicit expressions are obtained. The offset measurement noise is shown to be autocorrelated. Improved state variable models for tracking the target centroid are proposed. Subpixel tracking accuracy is achieved. >
01 Jun 1992
TL;DR: This paper applies image enhancement techniques on noise-bits-removed images and demonstrates visually that the removal of noise bits has no effect on the image property.
Abstract: Our previous studies used statistical methods to assess the noise level in digital images of various radiological modalities. We separated the pixel data into signal bits and noise bits and demonstrated visually that the removal of the noise bits will not affect the image quality. In this paper we apply imageenhancement techniques on noise-bits-removed images and demonstrate that the removal of noise bitshas no effect on the image property. The image processing techniques used are gray-level look up tabletransformation, Sobel edge detector, and 3-D surface display. Preliminary results show no noticeable . difference between original image and noise bits removed image using look up table operation and Sobeledge enhancement. There is slightly enhancement of slicing artifact in the 3-D surface display of thenoise bits removed image. 1. INTRODUCTION All images are subject to many different types of noise. The noise carries no useful information and deteriorates the image quality. Some of the components of noise are independent of the image