Showing papers on "Dark-frame subtraction published in 2001"

System for manipulating noise in digital images

Abstract: An apparatus for analyzing the broadband noise content of a digital image comprising the following: a means of automatically identifying regions of originally constant color in the image by analysis of the variance of pixel values of regions of the image; a means of automatically detecting and discarding regions deemed to be unrepresentative of the true noise content of an image, including under- and over- exposed regions; a means of allowing the user to manually select some or all required constant color regions if desired; and, a means of analyzing such constant color regions to generate a parametric or non-parametric model of the noise in the image, including frequency characteristic within and between channels and other characteristics such as phase which might describe structured noise.

A multiresolution based method for removing noise from digital images

Abstract: A method of removing noise from a digital image including receiving an original digital image including a plurality of pixels; generating at least one residual digital image and at least one base digital image from the original digital image, the base digital image having a lower spatial resolution than the original digital image; and generating a noise reduced base digital image by removing noise from the base digital image with a noise reduction filter so that when the noise reduced base digital image is combined with the residual digital image to produce a reconstructed digital image, noise is not present in the reconstructed digital image.

Visualization of pass-by noise by means of moving frame acoustic holography.

Abstract: The noise generated by pass-by test (ISO 362) was visualized. The moving frame acoustic holography was improved to visualize the pass-by noise and predict its level. The proposed method allowed us to visualize tire and engine noise generated by pass-by test based on the following assumption; the noise can be assumed to be quasistationary. This is first because the speed change during the period of our interest is negligible and second because the frequency change of the noise is also negligible. The proposed method was verified by a controlled loud speaker experiment. Effects of running condition, e.g., accelerating according to ISO 362, cruising at constant speed, and coasting down, on the radiated noise were also visualized. The visualized results show where the tire noise is generated and how it propagates.

On the reduction of impulsive noise in multichannel image processing

Abstract: A new approach to the problem of impulsive-noise reduction for color images is introduced. The major advantage of the technique is that it filters out the noise component while adapting itself to the local image structures. In this way the algorithm is able to eliminate strong impulsive noise while preserving edges and fine image details. As the algorithm is a fuzzy modification of the commonly used vector median operator, it is very fast and easy to implement. Our results show that the proposed method outperforms all standard algorithms for the reduction of impulsive noise in color images. © 2001 Society of Photo-Optical Instrumenta- tion Engineers. (DOI: 10.1117/1.1367347)

Image input apparatus having addition and subtraction processing

Abstract: Image data having a high S/N ratio is obtained even when the exposure time is relatively long. To achieve the above object, there is provided an image input apparatus in which an accumulation mode is set with the shutter open, thereby acquiring image data A1. The shutter is then closed, and the accumulation mode is set to acquire subtraction data between the image data and black image data A2. This processing is repeated to acquire image data A1 and subtraction data A2, and these subtraction data are added. These operations A1, A2, and A3 are repeated a predetermined number of times to update addition data, and image processing is performed on the basis of the updated addition data.

Reinforced spectral subtraction method to enhance speech signal

Abstract: We propose a speech enhancement technique. It is based on the spectral subtraction method, which is one of the major techniques of speech enhancement. However, the enhanced output speech signal of the spectral subtraction method is corrupted by "musical noise". The musical noise is an offensive noise for human listening. To reduce the musical noise, we adopt an iterative algorithm. The iterative algorithm is derived from the same idea as Wiener filtering for speech enhancement. We use the output signal of the spectral subtraction method as the input signal again. This process is iterated a few times. Each time we iterate the spectral subtraction method, we estimate the noise signal and subtract it. Therefore we can further reduce the musical noise with each iteration.

Method and apparatus for filtering noise from a digital image

Abstract: As is known in the art, it becomes progressively difficult to identify an image region as being caused by noise as the area of that image region increases. The present invention encompasses the discovery that image data associated with smaller noise regions tends to mirror image data associated with larger noise regions. In accordance with the present invention, known techniques are used to accurately identify smaller noise regions. The image data extracted from these smaller noise regions is then used to aid in the identification of larger noise regions. Accordingly, the present invention increases the area of noise regions capable of being accurately identified compared to prior art noise identification techniques. Once large and small noise regions have been identified, the noise regions can be filtered using techniques known in the art.

Adaptive filtering for image denoising

Abstract: This paper presents an adaptive image filter that reduces the amount of noise in images acquired by digital still camera sensors in a Bayer pattern format. The filter acts mainly on the high spatial frequency components of the image in all the areas where they are not perceived by the human visual system (HVS); thus it is an adaptive filter that improves the image quality.

Contrast focus figure-of-merit method that is insensitive to scene illumination level

Abstract: A method, system and program product for providing automatic focus adjustment for an image device, comprising the steps of: differentiating an image along some axis to obtain a difference image; computing a variance of the difference image; determining a noise contribution to the variance; subtracting the noise contribution from the variance; using the adjusted noise variance as a factor in making the automatic focus adjustment. In a preferred embodiment, the variance is normalized, and the noise contribution is determined by determining the shot noise and the read noise.

Method of removing noise from image signal

Abstract: In order to provide a noise removal method for removing noise signals mixed into an image signal without deteriorating picture quality of the overall image, such zigzag noise signals that the difference between the output levels of two pixels adjacent to each other along a noise generation direction alternately takes positive and negative vales at least three times are detected from noise signals mixed into an image signal. Then, a specific pixel is noted among a plurality of pixels corresponding to the noise signals, for calculating a mean value of the output levels of the noise signals with reference to the specific pixel and correcting the output level of a noise signal corresponding to the said specific pixel with the said mean value.

Entropy-Based Dark Frame Subtraction

Abstract: Noise due to dark current is a serious limitation for taking long exposure time images with a CCD digital camera. Current solutions have serious drawbacks: interpolation of pixels with high dark current leads to smoothing effects or other artifacts – especially if a large number of pixels are corrupted. Due to the exponential temperature dependence of the dark current, dark frame subtraction works best for temperature controlled high end CCD imaging systems. On the physical level, two independent signals (charge generated by photons hitting the CCD and by the dark current) are added. Due to its random distribution, adding (or subtracting) the dark current noise signal increases the entropy of the resulting image. The entropy is minimal if the dark current signal is not present at all. A dark frame is a good representation of the dark current noise. As the generated dark current depends on the temperature equally for all pixels, a noisy image can be cleaned by the subtraction of a scaled dark frame. The scaling factor can be determined in an optimization step which tries to minimize the entropy of the cleaned image. We implemented a software system that effectively removes dark current noise even from highly corrupted images. The resulting images contain almost no visible artifacts since only the noise signal is removed. This extends the range of usable exposure times of digital cameras without temperature control systems by about one to two orders of magnitude.

Method of calculating noise from multiple digital images utilizing common noise characteristics

Abstract: A method of enhancing one or more digital images from a plurality of digital images that are believed to be affected by a common noise source includes receiving two or more source digital images that are believed to be affected by a common noise source; using the pixels of the received source digital images to calculate a noise characteristic value that relates to the noise present in the received source digital images; and using the noise characteristic value and the received source digital images to respectively calculate enhanced digital images for the one or more of the received source digital images.

Measurements of static noise in display images

Abstract: The appearance of noise on a display is an important usability issue. Sources of noise include electrical interference, display driver artifacts, resampling artifacts, transmission artifacts, compression artifacts, and any intrinsic noise artifacts produced within a display device. Issues for the severity of the noise problem include total magnitude of noise, noise spatial frequencies, proximity of the noise spatial frequencies of the desired information content and the human-eye response to that information content, uniformity of the distribution of noise, and appearance of any visible or regular patterns in the noise. Whatever the source, an accurate method to measure noise may be required to properly assess the influence of the noise. We investigate the intricacies of using a digital camera to accurately measure noise in a static image on a flat panel display (FPD). The electro- optical transfer function of the FPD is measured. A known noise pattern is displayed and measured using the digital camera whereby the predicted noise is compared to the measured noise. Complications and limitations in the metrology will be discussed.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Method and apparatus for pseudo-random noise generation based on variation of intensity and coloration

Abstract: A method and apparatus for dithering for color computer display systems includes the addition of a noise component to each of the color components of each pixel in a pseudo-random manner. The noise component is preferably different for each color component. Taking the image as a whole, the noise component repeats on a regular basis but is preferably selected so as not to repeat on adjacent pixels. The image is divided into squares of pixels and the same noise component is added to each of the same relative pixels from square to square. The preferred square of pixels is four pixels wide by four pixels high. The value of the noise component is chosen such that the most significant bit alternates both horizontally and vertically from pixel to pixel within the square of pixels. The other bits of the value of the noise component are preferably chosen such that the value of the noise component does not repeat within the square of pixels and such that a simplified hardware implementation is made possible by their selection. The resulting hardware implementation preferably consists of a number of exclusive-or gates tied together to produce the value of the noise component based on the least significant bits of the X and Y coordinates of each pixel. This hardware implementation is simple enough that it becomes economically practical to add a different noise component to each of the three color components of each pixel rather than the same noise component to all of the color components.

Noise reduction in an image capturing device

Abstract: An image capturing device includes an electronic image sensor and a memory including a dark frame buffer that stores one or more dark frames generated by the electronic image sensor. A processor controls the electronic image sensor to substantially continuously capture and store a newest dark frame from the electronic image sensor when the electronic image sensor is not performing an image capture. The processor subtracts the newest dark frame from an image upon an image capture.

Removal of impulse noise from highly corrupted images by using noise position information and directional information of image

Abstract: In this paper, a new progressive switching type filter is proposed in order to restore images corrupted by salt-pepper impulse noise. The algorithm consists of two main processes: 1) noise detection - an impulse detection algorithm is used before filtering, a noise position image is obtained and 2) noise filtering - disturbed pixels are only filtered by using the noise position image. In this paper, we study the second process (i.e., noise filtering). In the past, the median filter is used for the second process. In this paper, we introduce a weighted average (WA) filter into second process. Using the directional property of input images derives the weights of the WA filter. Therefore, better restoration results are expected. Simulation results demonstrate that the proposed method is superior to the conventional filters which used the median filter in the second process.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Method and system for detecting object with specific motion on celestial sphere (debris or the like on stationary orbit)

Abstract: PROBLEM TO BE SOLVED: To provide a data processing method that can detect dark debris without interference by background noise in a fixed star tracking mode suitable to a wide-ranging observation. SOLUTION: For an arbitrary point P0 on an image, a point P1 where an object of observation point-imaged at an exposure start time is imaged at an exposure end time is computed, and an image output on a line joining the points P0 to P1 on image data is added. This process is carried out for every point in the image. Before the addition of the image data on the line joining the points P0 to P1, a level of noise is determined, and a high-density image of a celestial body in the image data is replaced with the noise level to erase the star image. The noise level may be determined through the computation of a peak value of a histogram of data on the processed region of the image.

Factors influencing image quality in digital radiographic systems

Abstract: The image quality of digital radiography systems is influenced by the interplay of many sources of image degradation. These include technology-dependent sources of image blur and noise. This paper systematically investigates the relative influence of the most common sources of image degradation for the entire digital radiography image chain including the detector, image processing and display using well established methods based on linear systems theory. Image quality is quantified in terms of NEQ and DQE. Baseline data are taken from experimental blur and noise measurements from several digital radiography systems, state-of-the-art image processing algorithms and current displays. A generalized theoretical model is exercised to demonstrate the relative importance of the intrinsic noise sources for both direct- and indirect-conversion digital radiography technologies. Since clinical imaging requires a complete system, including a detector, image processing and display, the model is extended to predict the role of image processing and display. This demonstrates the importance of the choice of display parameters such as those that control grayscale rendering, equalization and edge restoration. In summary, the performance of digital radiography systems depends on the interplay of many sources of image degradation from capture to display. Their effects are shown to be interdependent.

System and method for selecting an image processing path using estimated appearance of noise

Abstract: A method and system for processing an image based on noise appearance in the image, includes the steps of and means for: forming a noise table representing noise magnitude vs. intensity of the image; providing a plurality of potential image processing paths, each path having at least one image transform; modifying the noise table according to the image transform(s) in the at least one image processing path to produce an output noise table, generating a noise metric from the output noise table, said noise metric representing the noise appearance of the image processed by the at least one image processing path; selecting one of the plurality of potential image processing paths based on the noise metric; and applying the selected image processing path to the image.

Entropy-Based Dark Frame Subtraction.

Abstract: Noise due to dark current is a serious limitation for taking long exposure time images with a CCD digital camera. Current solutions have serious drawbacks: interpolation of pixels with high dark current leads to smoothing effects or other artifacts – especially if a large number of pixels are corrupted. Due to the exponential temperature dependence of the dark current, dark frame subtraction works best for temperature controlled high end CCD imaging systems. On the physical level, two independent signals (charge generated by photons hitting the CCD and by the dark current) are added. Due to its random distribution, adding (or subtracting) the dark current noise signal increases the entropy of the resulting image. The entropy is minimal if the dark current signal is not present at all. A dark frame is a good representation of the dark current noise. As the generated dark current depends on the temperature equally for all pixels, a noisy image can be cleaned by the subtraction of a scaled dark frame. The scaling factor can be determined in an optimization step which tries to minimize the entropy of the cleaned image. We implemented a software system that effectively removes dark current noise even from highly corrupted images. The resulting images contain almost no visible artifacts since only the noise signal is removed. This extends the range of usable exposure times of digital cameras without temperature control systems by about one to two orders of magnitude.

Elimination of impulsive noise in images by means of the use of support vector machines

Abstract: In this work we present an efficient way to cancel the impulsive noise into images by using the Support Vector Machines (SVM). The suppression of impulsive noise is a classic problem in nonlinear processing, and the SVM are especially useful in this type of processing. In this new approach we use the classification and the regression based on SVM. By using the classifier we select the noisy pixels into the images and by using the regression we obtain a reconstruction value based on the neighboring pixels. The results obtained are comparable and, a lot of times, better than those from another "state-of-art" techniques. Besides, this new technique can be applied successfully to images with high noise ratios while maintaining the visual quality and the low reconstruction error. 1. INTRODUCTION Some times the images that we received have added an impulsive noise. This impulsive noise can be due to a noisy transmission channel or to imperfections of the sensor with which we obtain the images so that in some points a saturation takes place. The linear techniques are little effective in the reduction of this type of noise and as alternative they nonlinear techniques appear. A well-known nonlinear method is the median filter. The main disadvantage of this method is that it is applied on all the points of the image regardless of they are noisy or not. Then a blurring effect is produced specially with high rates of noise. This defect is common to other techniques dedicated to the elimination of impulsive noise. In [1] appears a technique in which substitution in the considered noisy pixels is made and the detection of these noisy pixels is implemented by means of the comparison with certain thresholds. The noisy pixels are replaced by means of a modified median filter, that in that work is called Rank Ordered Mean (ROM) and that does not use the noisy pixel to calculate the median. In this work, we made a similar scheme but the detection and the substitution of noisy pixels is made with SVM. Our method provides excellent results in "Peak Signal to Noise Ratio" (PSNR), that measures the reconstruction error, and in visual quality and maintenance of the edges even for very high rates of noise.

Noise spectrum subtraction method and system

Abstract: A method for reducing noise in a voice signal, and a voice operated system utilizing the same are presented. A noise component in a compressed digital signal representative of the voice signal is determined, and subtracted from the compressed digital signal.

Elimination of Image Noise with CCD Device Characteristics

Abstract: The analysis for the noise composition in CCD image is carried out according to the operating principle of CCD device. A complete Poisson-Gaussian noise model is set up, a reasonable simplification has been carried out according to the practical application cases and good application effects have been achieved. The corresponding compensation is implemented for the fuzzy case appeared in CCD imaging by use of maximum-likelihood estimate in the paper. The simplification for the model is finished and the practical case is given in the end.

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.

A new image compression method using noise bit removal

Abstract: For communication and storage efficiency, image data should be substantially compressed. The compression ratio is limited by noise, which degrades the correlation between pixels. Due to the statistical nature of X-rays and the electromagnetic field, medical images are contaminated with random noise. Because of this effect, considerable effort has been devoted to remove noise from medical images. In this study, we use standard deviation to evaluate the noise level and subsequently estimate the number of noisy bits for each pixel. By discarding these noisy bits, the compression ratio can be improved. This method was verified using a synthetic digital image and tested in various radiological image modalities. This technique can increase the ratio up to 3.9 for MRI from 2.5 without significantly affecting the image quality. This process will have a great impact on storage reduction, transmission rate and the speed of image display and manipulation.

Noise Analyzing and Signal Processing for Scientific Grade CCD Camera

Abstract: Aim\ In order to reduce the noise of scientific grade CCD camera and improve the image quality.Methods\ The noise characteristic of CCD image sensor analyzed. Noise suppression method and signal processing circuit are described and designed analyzed. Results\ The circuit can reduce the dark current noise and eliminate the reset noise effectively.Conclusion\ Experiments prove that the presented method can reduce noise, increase signal to noise ratio and improve image quality.

Restrain speckle noise of SAR image basedon wavelet package threshold method

Abstract: Speckle noise on synthetic aperture radar image is inevitable. Understanding the SAR image becomes very hard because of the existence of speckle noise, and thus the application of SAR image is influenced severely. There are many methods to restrain the speckle noise in image domain. In frequency domain, there are methods based on FFT transform and WT transform. In this paper, according to the special characteristics of SAR image of desert area, a method based on wavelet package is proposed and compared with other filter methods. The image processing results show that this method restrains the noise effectively, and the edge information of the image is also retained well.

Noise Image Coding Using Soft-Threshold Based Denoising

Abstract: The soft threshold method proposed by Donoho is studied in this paper. The noise standard deviation of noise image and the thresholds of different scale are given. A separable 2 D wavelet filter is used so that the soft threshold denoising by Donoho is expediently applied to image processing, such as simultaneous denosing makes compression rate of a noisy image be large farthest. For noise image of nature scene and SAR, different image compression schemes are proposed respectively. Especially for SAR image, a natural logarithm transfors multiplicative noise to additive noise so that SAR image can be suppressed via the soft threshold denoising scheme. Experimental results show the decoded images by the soft threshold denoising have better quality than by the hard threshold denoising. It indicates that the improved ways in this paper are effective for noise image compression.

On the new filtering technique of noise attenuation in color images

Abstract: A new filter class for multichannel image processing is introduced and analyzed. The new technique of image enhancement is capable of reducing impulsive and Gaussian noise and it significantly outperforms the standard methods of noise reduction. In the paper, a smoothing operator, based on a random walk model and on a fuzzy similarity measure between pixels connected by a digital geodesic path, is introduced. The efficiency of the proposed method was tested on standard color images using objective image quality measures. Obtained results show that the new method not only outperforms standard noise reduction algorithms, but has some interesting features useful for segmentation of noisy color images.

Noise filtering of periodic image sequences

Abstract: This work describes a method for filtering image sequences degraded by noise, where the main object is moving with an almost periodic displacement. This object is assumed to be the only region of interest in the image, and tracking its movement against the background is the goal of the image processing. Under such circumstances, it is argued that a noise reduction strategy based on the knowledge of the motion will be more efficient than other classical methods for dynamic image sequences. This kind of problem is not unusual in the processing of scientific images, especially in the medical field. In this case the presence of noise is critical not only for the degradation of the visual quality, but also for the effectiveness of subsequent processing tasks, such as analysis and clinical interpretation.