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Showing papers on "Dark-frame subtraction published in 2008"


Journal ArticleDOI
TL;DR: The results from 100 test images showed that this proposed method surpasses some of the state-ofart methods, and can remove the noise from highly corrupted images, up to noise percentage of 95%.
Abstract: This paper presents a simple, yet efficient way to remove impulse noise from digital images. This novel method comprises two stages. The first stage is to detect the impulse noise in the image. In this stage, based on only the intensity values, the pixels are roughly divided into two classes, which are "noise-free pixel" and "noise pixel". Then, the second stage is to eliminate the impulse noise from the image. In this stage, only the "noise-pixels" are processed. The "noise-free pixels " are copied directly to the output image. The method adaptively changes the size of the median filter based on the number of the "noise-free pixels " in the neighborhood. For the filtering, only "noise-free pixels " are considered for the finding of the median value. The results from 100 test images showed that this proposed method surpasses some of the state-ofart methods, and can remove the noise from highly corrupted images, up to noise percentage of 95%. Average processing time needed to completely process images of 1600times1200 pixels with 95% noise percentage is less than 2.7 seconds. Because of its simplicity, this proposed method is suitable to be implemented in consumer electronics products such as digital television, or digital camera.

185 citations


Journal ArticleDOI
TL;DR: A comprehensive noise model for CCD cameras was used and a technique to identify and measure the prominent sources of sensor noise in commercially available charge-coupled device video cameras by analysis of the output images was presented.
Abstract: This paper presents a technique to identify and measure the prominent sources of sensor noise in commercially available charge-coupled device (CCD) video cameras by analysis of the output images. Noise fundamentally limits the distinguishable content in an image and can significantly reduce the robustness of an image processing application. Although sources of image sensor noise are well documented, there has been little work on the development of techniques to identify and quantify the types of noise present in CCD video-camera images. A comprehensive noise model for CCD cameras was used to evaluate the technique on a commercially available CCD video camera.

64 citations


Journal ArticleDOI
TL;DR: This study presents a comprehensive measurement of CCD digital-video camera noise, incorporating the effects of quantization and demosaicing, and shows the robustness and performance of an image-processing algorithm is fundamentally limited by sensor noise.
Abstract: This study presents a comprehensive measurement of CCD digital-video camera noise. Knowledge of noise detail within images or video streams allows for the development of more sophisticated algorithms for separating true image content from the noise generated in an image sensor. The robustness and performance of an image-processing algorithm is fundamentally limited by sensor noise. The individual noise sources present in CCD sensors are well understood, but there has been little literature on the development of a complete noise model for CCD digital-video cameras, incorporating the effects of quantization and demosaicing.

61 citations


Journal ArticleDOI
TL;DR: The purpose of this work is to characterize the radiation-induced noise and to develop filtration algorithms to restore image quality and to use a modified version of the adaptive switch filter in order to handle nonisolated groups of noisy pixels.
Abstract: Charge coupled devices (CCDs) are being increasingly used in radiation therapy for dosimetric purposes. However, CCDs are sensitive to stray radiation. This effect induces transient noise. Radiation-induced noise strongly alters the image and therefore limits its quantitative analysis. The purpose of this work is to characterize the radiation-induced noise and to develop filtration algorithms to restore image quality. Two models of CCD were used for measurements close to a medical linac. The structure of the transient noise was first characterized. Then, four methods of noise filtration were compared: median filtering of a time series of identical images, uniform median filtering of single images, an adaptive filter with switching mechanism, and a modified version of the adaptive switch filter. The intensity distribution of noisy pixels was similar in both cameras. However, the spatial distribution of the noise was different: The average noise cluster size was 1.2 +/- 0.6 and 3.2 +/- 2.7 pixels for the U2000 and the Luca, respectively. The median of a time series of images resulted in the best filtration and minimal image distortion. For applications where time series is impractical, the adaptive switch filter must be used to reduce image distortion. Our modified version of the switch filter can be used in order to handle nonisolated groups of noisy pixels.

61 citations


Journal ArticleDOI
TL;DR: An improved spectral subtraction method for the reduction of colored acoustic noise added to the speech in a helicopter cockpit or in a car caused by the engine sound is proposed.

58 citations


Patent
23 Sep 2008
TL;DR: In this article, a computer-implemented method for noise management in a digital image system measures noise levels of pixel data and adjusts the noise levels with at least one of an intensity gain setting, a spatial gain setting and a global gain setting.
Abstract: A computer-implemented method for noise management in a digital image system measures noise levels of pixel data. The noise levels are adjusted with at least one of an intensity gain setting, a spatial gain setting, and a global gain setting to calculate noise adaptive thresholds for use during spatial processing of the pixel data.

45 citations


Proceedings ArticleDOI
01 Dec 2008
TL;DR: A noise removal algorithm that can remove noise while retaining fine graphical elements is presented in this paper and the algorithm studies the neighborhood of thin lines before choosing to remove or retain it.
Abstract: Removing noise in engineering drawing images is important before applying image analysis processes. Noise should be removed while keeping the fine detail of the image intact. A noise removal algorithm that can remove noise while retaining fine graphical elements is presented in this paper. The algorithm studies the neighborhood of thin lines before choosing to remove or retain it. Real scanned images from GRECpsila03 and GRECpsila05 arc segmentation contests corrupted by 15% uniform salt/pepper noise are used in this experiment. Objective distortion measurements including PSNR and MSE show that our algorithm gives better quality images compared with other methods.

40 citations


Patent
Yunqiang Chen1, Tong Fang1, Sandra Martin1, Stefan Boehm1, Peter Durlak1 
03 Oct 2008
TL;DR: In this article, a method and system for intelligent digital subtraction can be used in a roadmap application for a coronary intervention, where a guide wire is inserted into the vessels, and a direct subtraction image is generated from the guide wire image and the mask image.
Abstract: A method and system for intelligent digital subtraction is disclosed. The method and system for intelligent digital subtraction can be used in a roadmap application for a coronary intervention. A mask image is obtained with vessels highlighted by contrast media. A guide wire is inserted into the vessels, and a guide wire image is obtained. A direct subtraction image is generated from the guide wire image and the mask image. A reduced noise subtraction image is generated based on mutual image information between the subtraction image and the guide wire image and mutual image information between the subtraction image and the mask image.

33 citations


Patent
27 Mar 2008
TL;DR: In this paper, an image denoising system and method of implementing the image denoing system is described, which is decomposed within each channel into frequency bands, and sub-band noise is propagated.
Abstract: An image denoising system and method of implementing the image denoising system is described herein. Noise is decomposed within each channel into frequency bands, and sub-band noise is propagated. Denoising is then able to occur at any node in a camera pipeline after accurately predicting noise that is signal level-dependent, frequency dependent and has inter-channel correlation. A methodology is included for estimating image noise in each color channel at a sensor output based on average image level and camera noise parameters. A scheme is implemented for detecting a peak-white image level for each color channel and predicting image level values for representative colors. Based on a noise model and camera parameters, noise levels are predicted for each color channel for each color patch and these noise levels are propagated to the denoising node. A three dimentional LUT correlates signal level to noise level. Then, a denoising threshold is adaptively controlled.

32 citations


Patent
23 Apr 2008
TL;DR: The image quality of an image frame from a CMOS image sensor array operated in global shutter mode may be enhanced by dispersing or randomizing the noise introduced by leakage currents from floating drains among the rows of the image frame.
Abstract: The image quality of an image frame from a CMOS image sensor array operated in global shutter mode may be enhanced by dispersing or randomizing the noise introduced by leakage currents from floating drains among the rows of the image frame Further, the image quality may be improved by accounting for time dependent changes in the output of dark pixels in dark pixel rows or dark pixel columns In addition, voltage and time dependent changes in the output of dark pixels may also be measured to provide an accurate estimate of the noise introduced to the charge held in the floating drains Such methods may be employed individually or in combination to improve the quality of the image

32 citations


Proceedings ArticleDOI
TL;DR: In this paper, the authors present data for the dark current of a commercially available CMOS image sensor for different gain settings and bias offsets over the temperature range of 295 to 340 K and exposure times of 0 to 500 ms.
Abstract: We present data for the dark current of a commercially available CMOS image sensor for different gain settings and bias offsets over the temperature range of 295 to 340 K and exposure times of 0 to 500 ms. The analysis of hot pixels shows two different sources of dark current. One source results in hot pixels with high but constant count for exposure times smaller than the frame time. Other hot pixels exhibit a linear increase with exposure time. We discuss how these hot pixels can be used to calculate the dark current for all pixels. Finally, we show that for low bias settings with universally zero counts for the dark frame one still needs to correct for dark current. The correction of thermal noise can therefore result in dark frames with negative pixel values. We show how one can calculate dark frames with negative pixel count.

Patent
22 Aug 2008
TL;DR: In this article, a method for eliminating noise from an image generated by an image sensor, including a central pixel intended to eliminate the noise in the image and peripheral pixels arranged around the central pixel, is proposed.
Abstract: A method for eliminating noise from an image generated by an image sensor, includes: setting a group of pixels arranged in a square matrix and including a central pixel intended to eliminate the noise in the image and peripheral pixels arranged around the central pixel; obtaining absolute difference values between a luminance value of the central pixel and a luminance value of the peripheral pixels according to directionalities of the peripheral pixels about the central pixel; comparing the obtained absolute difference values with first critical values to determine a region to which the central pixel belongs; when the determined region is the contour region, eliminating noise of the group of the pixels according to directionality of the contour; and when the determined region is the noise region, eliminating the noise of the group of the pixels according to a noise level of the group of the pixels.

Patent
23 Jun 2008
TL;DR: In this article, a system and method of reducing noise in output image data is provided, where pixels which may produce noise are identified, and a mask associated with the image data are generated.
Abstract: A system and method of reducing noise in output image data is provided. Grayscale image data having a plurality of pixels is received and processed. During processing, pixels which may produce noise are identified, and a mask associated with the image data is generated. The mask provides information related to the pixels, such as opaque and transparent regions for overlaying the pixels. The image data and the mask are compressed and stored. The mask assists in preventing the identified pixels from being visible when the image data is output, thereby reducing the noise in the image.

Proceedings ArticleDOI
16 Mar 2008
TL;DR: This research used Spectral Subtraction as a method to remove noise from speech signals using the fast Fourier transform and had recourse to the speech to noise ratio (SNR) in order to evaluate the performance of the proposed algorithm.
Abstract: We used Spectral Subtraction in this research as a method to remove noise from speech signals. Initially, the spectrum of the noisy speech is computed using the fast Fourier transform (FFT), then the average magnitude of the noise spectrum is subtracted from the noisy speech spectrum. We applied Spectral Subtraction to the speech signal "Hot dog" to which we digitally added vacuum cleaner noise. We implemented the noise removal algorithm by storing the noisy speech data into Hanning time-widowed half-overlapped data buffers, computing the corresponding spectrums using the FFT, removing the noise from the noisy speech, and reconstructing the speech back into the time domain using the inverse fast Fourier transform (IFFT). We had recourse to the speech to noise ratio (SNR )in order to evaluate the performance of the proposed algorithm.

Proceedings ArticleDOI
20 Dec 2008
TL;DR: An algorithm based on the local feature of the image to eliminate Gaussian noise is introduced, and this method overcomes the defects of traditional methods.
Abstract: The traditional removing algorithm of Gaussian noise can only reduce the effect of noise rather than remove it. Furthermore, the noise points in the image will diffuse after removing. According to the effect of the Gaussian noise on the visual images, this paper introduces an algorithm based on the local feature of the image to eliminate Gaussian noise, and this method overcomes the defects of traditional methods. Firstly, we categorize the location of the pixels into three classes-on the noise point, on the edge, and in the local texture, based on the local continuous smoothing in the image. Secondly, we can extract the edge information and texture of the image by morphology according to the local continuity of the image edge and texture property, then we can accurately locate the noise points of the image. Lastly, we use adaptive neighborhood to eliminate the other noise points. Comparing to the traditional methods, this algorithm can remove the noise better and have satisfying image visual impression.

Patent
Yi-Jen Chiu1
25 Mar 2008
TL;DR: In this article, a method of filtering noise from a picture may include determining a set of pixel noise metrics for selected pixels in the picture based solely on information from the set of selected pixels.
Abstract: A method of filtering noise from a picture may include determining a set of pixel noise metrics for a set of selected pixels in the picture based solely on information from the set of selected pixels in the picture. The method may also designate as valid a subset of pixel noise metrics in the set of pixel noise metrics whose associated pixels are not located at an edge or are not located in a complicated area of the picture. A set of block noise metrics may be calculated from the valid subset of pixel noise metrics, and a global noise metric for the picture may be ascertained from the set of block noise metrics. The picture may be filtered using the global noise metric to generate a filtered picture.

Journal ArticleDOI
TL;DR: This algorithm treats multichannel images as a vector class and takes both magnitude and phase angles of the pixel vectors into consideration, resulting in an efficient noise detector based on pixel vector angle statistics and impulse noise filtering with a hybrid of vector magnitude and vector angle function.
Abstract: This paper proposes a robust approach to color image noise removal that efficiently eliminates noisy pixels by exploiting several vector-class characteristics of multichannel pixels. This algorithm treats multichannel images as a vector class and takes both magnitude and phase angles of the pixel vectors into consideration. It consists of two steps: an efficient noise detector based on pixel vector angle statistics and impulse noise filtering with a hybrid of vector magnitude and vector angle function. Extensive experimental results demonstrate that the proposed approach significantly outperforms several other well-known techniques for color image noise removal.

Patent
Masanori Hara1
14 Jan 2008
TL;DR: In this paper, a character noise eliminating apparatus was proposed to eliminate a character's noise when a fingerprint ridgeline area has a higher density than the character noise area, where a character can be eliminated when the character's density is higher than the fingerprint's density.
Abstract: To provide a character noise eliminating apparatus that can eliminate a character noise when a fingerprint ridgeline area has a higher density than a character noise area. A character noise eliminating apparatus includes a device for repeating a processing in which a binary image is generated by binarizing an image with a binarization threshold that is inputted by an operator and the binary image is displayed on a data display device, and determining the character noise area, a device for setting density conversion area layers inside and outside the character noise area, and a device for setting a neighboring pixel group within the same density conversion area layer as the density conversion area layer to which a target pixel belongs as a reference area of the target pixel, with respect to pixels in the density conversion area layers, and generating a density converted image applying a local image enhancement.

Patent
24 Jul 2008
TL;DR: The radiation image pickup apparatus of as discussed by the authors can obtain an accurate temperature characteristic of dark current noise by obtaining dark image signals at varied times for accumulating in capacitors charge signals converted by an X-ray converting layer.
Abstract: The radiation image pickup apparatus of this invention can obtain an accurate temperature characteristic of dark current noise, the dark current noise being caused by dark current flowing through an X-ray conversion layer, by obtaining dark image signals at varied times for accumulating in capacitors charge signals converted by an X-ray converting layer. Consequently, the noise due to the dark current can be removed with high accuracy by removing periodically acquired offset signals from X-ray detection signals acquired at a time of X-ray image pickup, and correcting variations of the dark current noise due to a difference in temperature between a time of offset signal acquisition and the time of X-ray image pickup, using the temperature characteristic of the dark current noise.

Patent
Yaowu Mo1, Chen Xu2
25 Jan 2008
TL;DR: In this paper, the authors provide pixel-wise noise correction using pixels to provide reference values during pixel readout operations, using pixel-level noise correction as a reference value during pixel reading operations.
Abstract: Methods and apparatuses providing pixel-wise noise correction using pixels to provide reference values during pixel readout operations.

Journal ArticleDOI
TL;DR: The filter was found to have the potential to reduce the patient dose by reducing the noise in dynamic as well as static X-ray images and was demonstrated in fluoroscopic, digital subtraction angiography (DSA) and mammographic phantom studies.
Abstract: A real-time digital filter for noise reduction in X-ray images is proposed. The filter is based on averaging of only similar pixels (pixels that differ only little) rather than neighboring pixels, which are averaged in conventional linear low-pass filters. The effectiveness of the filter was evaluated by computer simulation, where original images that were acquired by X-ray exposure were processed in accordance with the filter algorithm. The resulting images were evaluated in terms of the pre-sampled modulation transfer function (MTF), the noise power spectrum (NPS), and the lag. Comparison of the filtered and original images revealed that the NPS was reduced for the full range of spatial frequencies in the filtered image, resulting in a reduction of total noise power to about 1/9 the level in the original image with no degradation in the MTF or lag. The usefulness of the filter was demonstrated in fluoroscopic, digital subtraction angiography (DSA) and mammographic phantom studies. The filter was found to have the potential to reduce the patient dose by reducing the noise in dynamic as well as static X-ray images.

Patent
Wei Hong1
12 Dec 2008
TL;DR: In this paper, a noise filter method and apparatus for producing at least one of a video or an image with reduced noise is presented, which includes performing a low pass filter on the noise level according to the noise estimation, performing spatial filtration on the frame, performing motion detection on a spatially filtered frame, determining motion-to-blending factor conversion and, accordingly, performing frame blending, and outputting a frame with reduced noises.
Abstract: A noise filter method and apparatus for producing at least one of a video or an image with reduced noise. The noise filter method includes performing noise estimation on a frame of at least one of an image or video and applying a low pass filter on the noise level according to the noise estimation, performing spatial filtration on the frame, performing motion detection on a spatially filtered frame, determining motion-to-blending factor conversion and, accordingly, performing frame blending, and outputting a frame with reduced noise.

01 Jun 2008
TL;DR: This paper deals with advanced methods for elimination of thermally generated charge in astronomical images, which were acquired by a Charged Coupled Device (CCD) sensor, whereas an extensive measurement on an astronomical camera was proposed and done.
Abstract: This paper deals with advanced methods for elimination of thermally generated charge in astronomical images, which were acquired by a Charged Coupled Device (CCD) sensor. There exist a number of light images acquired by telescope, which were not corrected by dark frame. The reason is simple: the dark frame doesn’t exist, because it was not acquired. This situation may for instance come when sufficient memory space is not available. Correction methods based on the modeling of the light and dark image in the wavelet domain will be discussed. As the model for the dark frame image and for the light image the generalized Laplacian was chosen. The model parameters were estimated using moment method, whereas an extensive measurement on an astronomical camera was proposed and done. This measurement simplifies estimation of the dark frame model parameters. Finally a set of astronomical testing images was corrected and then the objective criteria for an image quality evaluation based on the aperture photometry were applied.

Journal ArticleDOI
TL;DR: The performance of uniform and nonuniform detector arrays for application to the PANOPTES (processing arrays of Nyquist-limited observations to produce a thin electro-optic sensor) flat camera design is analyzed for measurement noise environments including quantization noise and Gaussian and Poisson processes.
Abstract: The performance of uniform and nonuniform detector arrays for application to the PANOPTES (processing arrays of Nyquist-limited observations to produce a thin electro-optic sensor) flat camera design is analyzed for measurement noise environments including quantization noise and Gaussian and Poisson processes. Image data acquired from a commercial camera with 8 bit and 14 bit output options are analyzed, and estimated noise levels are computed. Noise variances estimated from the measurement values are used in the optimal linear estimators for superresolution image reconstruction.

Patent
29 Apr 2008
TL;DR: In this paper, an image noise measurement system performs a noise estimation on a current image and a storage device stores a previous image, and a recursive filter performs a recursive filtering operation on the noise estimation index according to the confident level index to produce a noise estimate for the current image.
Abstract: An image noise measurement system performs a noise estimation on a current image. A storage device stores a previous image. A noise estimator performs a noise estimation on sub-areas of the current image and the previous image to thereby produce a noise estimation index for the sub-area of the current image. A distribution calculator calculates a distribution of positive and negative signs of pixel differences in the sub-areas of the current image and the previous image to thereby output a positive sign number and a negative sign number. A confidence generator produces a confident level index according to the positive sign number and the negative sign number. A recursive filter performs a recursive filtering operation on the noise estimation index according to the confident level index to thereby produce a noise estimate for the current image.

Journal Article
TL;DR: An improved method based on PCNN, according to the operating theory of PCNN and the characters of noise is proposed, which is perfect for image with noise of salt and pepper and has a good ability in keeping the details of image.
Abstract: The removal of image noise is always a difficult problem in the field of image processing.Conventional methods,which may make the image blurred,are mainly used for denoising of binary image,cannot be applied for gray image.For solving this problem,the paper proposes an improved method based on PCNN,according to the operating theory of PCNN and the characters of noise.The computer simulation experiment result proves that the method is perfect for image with noise of salt and pepper and has a good ability in keeping the details of image.This is very benficial to image restoration and image recognition.However,the method is not perfect for image with serious gauss noise and so it is to be improved.

Proceedings ArticleDOI
TL;DR: In this article, the authors investigated whether the dark current produced in an image taken with a closed shutter is identical to the one generated in an exposure in the presence of light, and found that some pixels produce a different amount of dark current under illumination.
Abstract: Thermal excitation of electrons is a major source of noise in Charge-Coupled Device (CCD) imagers. Those electrons are generated even in the absence of light, hence the name dark current. Dark current is particularly important for long exposure times and elevated temperatures. The standard procedure to correct for dark current is to take several pictures under the same condition as the real image, except with the shutter closed. The resulting dark frame is later subtracted from the exposed image. We address the question of whether the dark current produced in an image taken with a closed shutter is identical to the dark current produced in an exposure in the presence of light. In our investigation, we illuminated two different CCD chips to different intensities of light and measured the dark current generation. A surprising conclusion of this study is that some pixels produce a different amount of dark current under illumination. Finally, we discuss the implications that this has for dark frame image correction.

Proceedings ArticleDOI
Cangju Xing1
27 May 2008
TL;DR: An effective method for removing heavy salt-and-pepper noise is proposed in this paper, which includes three steps: the noise pixels are distinguished from the signal pixels; then set initial values for noise pixels; finally, compute the output.
Abstract: An effective method for removing heavy salt-and-pepper noise is proposed in this paper. This method includes three steps. In the first step, the noise pixels are distinguished from the signal pixels; then set initial values for noise pixels; finally, compute the output. The main difference from other switch-type filters is the means to change the values of the contaminated noise pixels. The proposed scheme is very effective, especially for heavily contaminated image. It can remove salt-and-pepper noise with a noise level as high as 95%, and it's relatively fast.

Proceedings ArticleDOI
08 Dec 2008
TL;DR: A new method that works well with different signal to noise ratios ranging from -1.58 dB to 20 dB is presented and is capable of dealing with the wide range of Gaussian noise and gives consistent performance throughout.
Abstract: Night vision systems have become an important research area in recent years. Due to variations in weather conditions such as snow, fog, and rain, night images captured by camera may contain high level of noise. These conditions, in real life situations, may vary from no noise to extreme amount of noise corrupting images. Thus, ideal image restoration systems at night must consider various levels of noise and should have a technique to deal with wide range of noisy situations. In this paper, we have presented a new method that works well with different signal to noise ratios ranging from -1.58 dB to 20 dB. For moderate noise, Wigner distribution based algorithm gives good results, whereas for extreme amount of noise 2nd order Wigner distribution is used. The performance of our restoration technique is evaluated using MSE criteria. The results show that our method is capable of dealing with the wide range of Gaussian noise and gives consistent performance throughout.

Journal Article
TL;DR: In this article, an improved adaptive median filter is proposed to restore images corrupted by impulse noise, which can detect noise with high accuracy, remove noise efficiently while retaining image details, especially to images with high noise density.
Abstract: An improved adaptive median filter is proposed to restore images corrupted by impulse noiseThere are mainly three improved points in this algorithmFirst,the image pixels are classified into signal pixels and noise pixels according to the decision criterionSecond,a measure,denoted as minimum set distance,is introduced to avoid misclassification of high frequency signal as noiseThird,the median of minimum uncorrupted pixel set is used to restore noise pixel,in order to eliminate its neighborhood noise impactThe results of comparison experiments with RAMF and NASMF demonstrate that the proposed method can detect noise with high accuracy,remove noise efficiently while retaining image details,especially to images with high noise density