Showing papers on "Dark-frame subtraction published in 1996"

Image noise reduction system using a wiener variant filter in a pyramid image representation

Abstract: The invention relates to a novel process and system for removing noise from an image by first noise modeling an image signal source to generate noise masks and LUT values characteristic of noise at different frequency levels for each channel, and then applying the stored noise masks and LUT values to an image signal for noise removal. The image is first captured as an electronic image signal by the image signal source, then represented by a pyramid structure whereby each successive level of the pyramid is constructed from DC values of the previous level, and each level of the pyramid corresponds to a different frequency band of the image signal. A Wiener variant filter using DCT transforms is used to filter DCT coefficients at each level. The image is restored with reduced noise by replacing DC values with next level IDCT coefficients then performing an IDCT on the results.

Noise filtering in solar speckle masking reconstructions

Abstract: A new method of obtaining a sensitive noise filter for solar speckle masking reconstructions is presented below. This filter separates the true image information from noise most reliably. Its efficiency is demonstrated by some representative examples considering observed and artificial image data which were generated in a computer. The latter set of data also suffered realistic degradations by the influence of seeing and noise taken from suitable observations.

Extended spectral subtraction

Abstract: This paper describes a new method for one channel noise suppression system which overcomes the typical disadvantage of one channel noise suppression algorithms — the impossibility of noise estimation during speech sequence. Our method is the combination of Wiener filtering and spectral subtraction. The noise can be successfully updated even during the speech sequences and that is why there is no need of the voice activity detector.

System and method for selectively noise-filtering digital images

Abstract: A system and method for noise filtering digital images is implemented in an automated image enhancement system without significantly reducing the performance of the automated image enhancement system. The system and method trigger a noise filter based on image measurements. If the image measurements indicate that the likelihood of objectionable "noise" in the image is high, a noise filter is triggered. Otherwise the noise filter is not triggered. In this way, only images that are in need of noise filtering are filtered, while other images are processed without the additional performance overhead required by the noise filter.

Method of image noise reduction processing

Abstract: A method of noise reduction processing for reducing noise generated when an image of a photographic film is converted to a digital image signal includes the steps of: measuring a large area transmission density of each of a plurality of image frames recorded on the photographic film; classifying measured values of the large area transmission density into a plurality of groups; reading the image signals of the same image frame by an amount corresponding to the number of inputs of the image signals of the same image frame set in advance for each of the classified groups; and subjecting the image signals of the same image frame which have been read to averaging processing.

Statistics of both optical and electrical noise in digital volume holographic data storage

Abstract: The authors analyse the statistics of optical and electrical noise in holographic data storage and present closed form expressions of the threshold value and the bit-error-rate (BER). The results indicate that depending on the percentage of the two types of noise, the threshold value should be adjusted and the BER varies.

Correction of background noise in direct digital dental radiography.

Abstract: OBJECTIVES To clarify the source of noise in direct digital intra-oral radiography with RVG-S (Trophy Radiologie, Vincennes, France) and to use these to develop a method for correction of background noise. METHODS Sensor temperature, image acquisition time and X-ray dose were independently analysed with the IPLab Spectrum (Signal Analytics, Vienna, VA) software. RESULTS The decrease in pixel value due to the dark current was linearly related to the image acquisition time. Although a variation in sensitivity was observed when the sensor was exposed to X-rays, the mean pixel value of the entire image was linearly related to the exposure time. The image showing only the signal due to X-ray dose was derived from the original RVG-S image by correcting for the dark current and the pixel-by-pixel sensitivity variation of the CCD sensor. CONCLUSION The image formed only by X-ray dose distribution can be derived by correcting for the background noise.

Measurement of quantum noise in fluoroscopic systems for portal imaging.

Abstract: In fluoroscopic portal imaging systems, a metal plate is bonded to a phosphor screen and together these act as the primary x‐ray sensor. The light from the screen is collected and imaged by a lens on the target of a video camera. The demagnification (M) between the large area of the phosphor being imaged and the small active area of the video camera results in poor optical coupling between the screen and the video camera. Consequently x‐ray quantum noise is small compared to other noise sources. By reducing the demagnification, the light from the screen is collected more efficiently, so we were able to increase the x‐ray quantum noise relative to other noise sources and thus unambiguously identify it. The noise power spectrum was measured as a function of M to determine the relationship between the x‐ray quantum noise, shot noise, and amplifiernoise. It was found by extrapolation to clinical demagnifications that the amplifiernoise dominates x‐ray quantum noise at all spatial frequencies, but the shot noise was less than the x‐ray quantum noise at low spatial frequencies. For low spatial frequencies, this implies that a secondary quantum sink can be avoided. If amplifiernoise could be sufficiently reduced, x‐ray quantum limited images could be obtained in clinical systems at low spatial frequencies.

Dual domain interactive image restoration: basic algorithm

Abstract: This paper describes a new fast, iterative algorithm for interactive image noise removal. Given the locations of noisy pixels and a prototype image, the noisy pixels are to be restored in a natural way. Most existing image noise removal algorithms use either frequency domain information (e.g. low pass filtering) or spatial domain information (e.g median filtering or stochastic texture generation). However, for good noise removal, both spatial and frequency information must be used. The existing algorithms that do combine the two domains (e.g. Gerchberg-Papoulis and related algorithms) place the limitation that the image be band-limited and the band limits be known. Also, some of these may not work well when the noisy pixels are contiguous and numerous. Our algorithm combines the spatial and frequency domain information by using projection onto convex sets (POCS). But unlike previous methods it does not need to know image band limits and does not require the image to be band-limited. Results given here show noise removal from images with texture and prominent lines. The detailed textures as well as the pixels representing prominent lines are created by our algorithm for the noise pixels. The algorithm is fast, the cost being a few iterations (usually under 10), each requiring an FFT, IFFT and copying of a small neighborhood of the noise.

Noise measurement technique for document scanners

Abstract: Scanner noise is one of the fundamental parameters of image quality. In this paper, we present an algorithm developed to derive the noise of a scanner using the 2D Wiener spectra of the test pattern and the scanner's MTF. The Wiener spectra of the test pattern was measured and its contribution to the measured RMS noise was estimated by integrating the volume under the product of the test pattern Wiener spectra and the scanner's MTF. The test pattern contribution was then removed from the measured noise. The derived noise agrees very well with the noise model for both drum scanner and CCD scanners. The structured 1D noise is also of interest especially when evaluating CCD scanner systems. A method was described to accurately determine 1D structured noise by averaging over fast scan and slow scan directions. Finally an experiment was conducted to verify the noise measurement technique. The true noise of a drum scanner was measured at its analog output terminal, and was compared to the noise estimated with the proposed new noise metric. The agreement between hardware measured noise and the estimated noise is very good with RMS error of less than 0.001 in reflectance unit. With this new technique, we can effectively improve the noise measurement accuracy by a factor of up to 500% for a photographic test pattern.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Electronic image pickup device

Abstract: PROBLEM TO BE SOLVED: To improve the performance and efficiency of a device by improving a fact that a memory with a high capacity is required to store dark frames and a scanning time of an image sensor is very long in the case of correcting a black pattern due to a dark current. SOLUTION: An electronic image pickup device is provided, where a charge moving type image sensor 18 corrects a black pattern due to a dark current. The image sensor 18 acquires a reference dark frame in the dark and a dark frame pixel value. An exposure section adjusts an exposure time of a pickup light to provide corresponding exposure to pluralities of image frames. Thus, the image sensor 18 generates pluralities of corresponding image frames each having a frame pixel value. Then a processor 38 obtains a reference coefficient from the dark frame pixel value, applies it to the frame pixel value of pluralities of the image frames to obtain the corrected image frame pixel values where the black pattern is corrected. Since the one reference dark frame exposure is employed for the correction of the exposure of lots of the image frames, the performance and the efficiency of the device are enhanced.

Photon-Limited Image Detection Using Shot-Noise Models.

Abstract: : The objective of this research continues to be the study of shot noise models and their application to the development of computationally feasible procedures for image detection problems. Also of interest is the performance evaluation of these procedures. These efforts are motivated by applications to low light level imaging as would occur in low dose x ray exposures or in night vision systems. Results are also be applicable to photon limited optical communication systems and to optical neural networks. Considerable progress has been made in understanding shot noise. The three major results of our research are (i) methods for computing shot noise distributions when both the intensity function and the system impulse response are known; (ii) methods for estimating an unknown intensity when only the impulse response is known; and (iii) methods for jointly estimating the intensity and the impulse response when both are unknown (a type of blind deconvolution).

Simulation of photon-limited images using video data

Abstract: Poisson or shot noise is a major degrading factor in low-light and infrared imaging The authors show how images from a standard video camera can be artificially degraded to simulate the effect of Poisson noise A specific algorithm is given, together with details of the computational cost

Adaptive Noise Suppression Using Digital Signal Processing

Abstract: A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately After spectra subtraction low amplitude signals are squelched A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate This is done by determining if the frame of data being sampled is a voiced or unvoiced frame During unvoice frames an estimate of the noise is obtained A running average of the noise is used to approximate the expected value of the noise Applications include the emergency egress vehicle and the crawler transporter

Optical Flickering and Shot Noise in AM Her Systems

Abstract: The emission from AM Her systems show a variety of time-variable phenomena, including flickering with a typical power spectrum slope of -1 to -2 The optical flickering is usually modeled as, or assumed to be, a shot noise process with many overlapping simultaneous shots Panek (1980) found that, for AM Her, a consistent model could be constructed with randomly occurring 70…90s rectangular shots The power spectrum had a v -2 shape above 002 Hz as expected, although it is not clear whether a break in the slope of the power spectrum was actually seen around 001 Hz There are many additional reports in the literature of ‘characteristic time-scales’ on the order of tens of seconds However we are not aware of any case where the reported time-scale has been supported by eg a break in the power density spectrum It is easy to show that the usual method of estimating a ‘characteristic time-scale’ from the auto correlation function of de-trended data will suggest such a characteristic time-scale even if none is present in the original time series The evidence for shot noise in AM Her light curves therefore needs a re-examination In this paper we give a short summary of our analysis of optical flickering in V834 Cen, based on high speed photometry obtained at ESO in 1987 Details will be reported elsewhere

Space-time-domain median filtering in low-light-level noise processing

Abstract: The random flicker noise is the main character of low-light- level (LLL) image, so the noise suppressing is a key technique for LLL image processing. In this paper, the noise sources and its characteristics of LLL image are studied, and varied existing noise processing techniques are analyzed. On the basis of these, a novel filtering approach, space-time domain median filter, is presented. In this approach, the time correlation of LLL TV image is utilized and the time domain median filter is combined with the space domain median filter. Therefore the LLL image noise is reduced significantly, and the quality of LLL image is improved greatly.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.