Median filtering: structure analysis and application

Median filtering is a simple digital non—linear signal smoothing operation in which median of the samples in a sliding window replaces the sample at the middle of the window. The resulting filtered sequence tends to follow polynomial trends in the original sample sequence. Median filter preserves signal edges while filtering out impulses. Due to this property, median filtering is finding applications in many areas of image and speech processing. Though median filtering is simple to realise digitally, its properties are not easily analysed with standard analysis techniques,

High-performance 3D median filter architecture for medical image despeckling

A high-sample rate 3D median filtering processor architecture is proposed, based on a novel 3D median filtering algorithm, that can reduce the computing complexity in comparison with the traditional bubble sorting algorithm. A 3 x 3 x 3 filter processor is implemented in VHDL, and the simulation verifies that the processor can process a 128 x 128 x 96 MRI image in 0.03 seconds while running at 50 MHz.

Image fusion based on median filters and SOFM neural networks: a three-step scheme

This paper presents a new image data fusion scheme by combining median filtering with self-organizing feature map (SOFM) neural networks. The scheme consists of three steps: (1) pre-processing of the images, where weighted median filtering removes part of the noise components corrupting the image, (2) pixel clustering for each image using self-organizing feature map neural networks, and (3) fusion of the images obtained in Step (2), which suppresses the residual noise components and thus further improves the image quality. It proves that such a three-step combination offers an impressive effectiveness and performance improvement, which is confirmed by simulations involving three image sensors (each of which has a different noise structure).

A post processing technique for improved harmonic/percussion separation in polyphonic speech

In this paper we propose a postprocessing technique for a spectrogram diffusion based harmonic/percussion decom- position algorithm. The proposed technique removes har- monic instrument leakages in the percussion enhanced out- puts of the baseline algorithm. The technique uses median filtering and an adaptive detection of percussive segments in subbands followed by piecewise signal reconstruction using envelope properties to ensure that percussion is enhanced while harmonic leakages are suppressed. A new binary mask is created for the percussion signal which upon applying on the original signal improves harmonic versus percussion separation. We compare our algorithm with two recent techniques and show that on a database of polyphonic Indian music, the postprocessing algorithm improves the harmonic versus percussion decomposition significantly.

数字图像处理中多窗口下的自适应中值滤波

根据心理物理学、神经生理学、认知神经学等学科在视觉认知领域的部分研究成果，结合机器视觉、图像处理领域在图像增强方面已经提出的一些方法，提出了结合先验知识的多窗口结构下的分块中值滤波方法，在每一个窗口内单独进行处理与分析，突出了视觉处理目的，减少了运算量， 节省数据存储空间，达到了令人满意的滤波效果，能够在原始图像比较复杂的情况下，较好地对其进行预处理，可以改善、提高后期图像处理过程，如图像分割、图像分析的正确性和有效性。

井间地震技术研究和应用

Cross well seismic technique is a new type of geophysical method, which observes the seismic wave of the geologic body by placing both the source and receiver in the wells. By applying this method, it averted the absorption to high-frequency component of seismic signal caused by low weathering layers, thus, an extremely high-resolution seismic signal can be acquired. And extremely fine image of cross well formations, structure, and reservoir can be achieved as well. An integrated research is conducted to the high-frequency S-wave and P-wave data and some other data to determine the small faults, small structure and resolving the issues concerning the thin bed and reservoir's connectivity, fluid distribution, steam injection and fracture. This method connects the high-resolution surface seismic, logging and reservoir engineering. In this paper, based on the E & P situation in the oilfield and the theory of geophysical exploration, a research is conducted on cross well seismic technology in general and its important issues in cross well seismic technology in particular. A technological series of integrated field acquisition, data processing and interpretation and its integrated application research were developed and this new method can be applied to oilfield development and optimizing oilfield development scheme. The contents and results in this paper are as listed follows: An overview was given on the status quo and development of the cross well seismic method and problems concerning the cross well seismic technology and the difference in cross well seismic technology between China and international levels; And an analysis and comparison are given on foreign-made field data acquisition systems for cross-well seismic and pointed out the pros and cons of the field systems manufactured by these two foreign companies and this is highly valuable to import foreign-made cross well seismic field acquisition system for China. After analyses were conducted to the geometry design and field data for the cross well seismic method, a common wave field time-depth curve equation was derived and three types of pipe waves were discovered for the first time. Then, a research was conducted on the mechanism for its generation. Based on the wave field separation theory for cross well seismic method, we believe that different type of wave fields in different gather domain has different attributes characteristics, multiple methods (for instance, F-K filtering and median filtering) were applied in eliminating and suppressing the cross well disturbances and successfully separated the upgoing and downgoing waves and a satisfactory result has been achieved. In the area of wave field numerical simulation for cross well seismic method, a analysis was conducted on conventional ray tracing method and its shortcomings and proposed a minimum travel time ray tracing method based on Feraiat theory in this paper. This method is not only has high-speed calculation, but also with no rays enter into "dead end" or "blinded spot" after numerous iterations and it is become more adequate for complex velocity model. This is first time that the travel time interpolation has been brought into consideration, a dynamic ray tracing method with shortest possible path has been developed for the first arrivals of any complex mediums, such as transmission, diffraction and refraction, etc and eliminated the limitation for only traveling from one node to another node and increases the calculation accuracy for minimum travel time and ray tracing path and derives solution and corresponding edge conditions to the fourth-order differential sonic wave equation. The final step is to calculate cross well seismic synthetics for given source and receivers from multiple geological bodies. Thus, real cross-well seismic wave field can be recognized through scientific means and provides important foundation to guide the cross well seismic field geometry designing. A velocity tomographic inversion of the least square conjugated gradient method was developed for cross well seismic velocity tomopgraphic inversion and a modification has been made to object function of the old high frequency ray tracing method and put forward a thin bed oriented model for finite frequency velocity tomographic inversion method. As the theory model and results demonstrates that the method is simple and effective and is very important in seismic ray tomographic imaging for the complex geological body. Based on the characteristics of the cross well seismic algorithm, a processing flow for cross well seismic data processing has been built and optimized and applied to the production, a good section of velocity tomopgrphic inversion and cross well reflection imaging has been acquired. The cross well seismic data is acquired from the depth domain and how to interprets the depth domain data and retrieve the attributes is a brand new subject. After research was conducted on synthetics and trace integration from depth domain for the cross well seismic data interpretation, first of all, a research was conducted on logging constraint wave impedance of cross well seismic data and initially set up cross well seismic data interpretation flows. After it applied and interpreted to the cross well seismic data and a good geological results has been achieved in velocity tomographic inversion and reflection depth imaging and a lot of difficult problems for oilfield development has been resolved. This powerful, new method is good for oilfield development scheme optimization and increasing EOR. Based on conventional reservoir geological model building from logging data, a new method is also discussed on constraining the accuracy of reservoir geological model by applying the high resolution cross well seismic data and it has applied to Fan 124 project and a good results has been achieved which it presents a bight future for the cross well seismic technology.

Model-based detection of spiculated lesions in mammograms

R. Zwiggelaar, T.C. Parr, J.E. Schumm. I.W. Hutt, S.M. Astley, C.J. Taylor and C.R.M. Boggis, 'Model-based detection of spiculated lesions in mammograms', Medical Image Analysis 3 (1), 39-62 (1999)

Robust multimodal face and fingerprint fusion in the presence of spoofing attacks

Anti-spoofing is attracting growing interest in biometrics, considering the variety of fake materials and new means to attack biometric recognition systems. New unseen materials continuously challenge state-of-the-art spoofing detectors, suggesting for additional systematic approaches to target anti-spoofing. By incorporating liveness scores into the biometric fusion process, recognition accuracy can be enhanced, but traditional sum-rule based fusion algorithms are known to be highly sensitive to single spoofed instances. This paper investigates 1-median filtering as a spoofing-resistant generalised alternative to the sum-rule targeting the problem of partial multibiometric spoofing where m out of n biometric sources to be combined are attacked. Augmenting previous work, this paper investigates the dynamic detection and rejection of livenessrecognition pair outliers for spoofed samples in true multi-modal configuration with its inherent challenge of normalisation. As a further contribution, bootstrap aggregating (bagging) classifiers for fingerprint spoof-detection algorithm is presented. Experiments on the latest face video databases (Idiap Replay- Attack Database and CASIA Face Anti-Spoofing Database), and fingerprint spoofing database (Fingerprint Liveness Detection Competition 2013) illustrate the efficiency of proposed techniques.

Proton diffusion tensor spectroscopy of metabolites in human muscle in vivo

PURPOSE To study the apparent diffusivity and its directionality for metabolites of skeletal muscle in humans in vivo by (1) H magnetic resonance spectroscopy. METHODS The diffusion tensors were determined on a 3 Tesla MR system using optimized acquisition and processing methods including an adapted STEAM sequence with orientation-dependent diffusion weighting, pulse-triggering with individually adapted delays, eddy-current correction schemes, median filtering, and simultaneous prior-knowledge fitting of all related spectra. RESULTS The average apparent diffusivities, as well as the fractional anisotropies of taurine (ADCav  = 0.74 × 10(-3) s/mm(2) , FA = 0.46), creatine (ADCav  = 0.41 × 10(-3)  s/mm(2) , FA = 0.33), trimethylammonium compounds (ADCav  = 0.48 × 10(-3)  s/mm(2) , FA = 0.34), carnosine (ADCav  = 0.46 × 10(-3)  s/mm(2) , FA = 0.47), and water (ADCav  = 1.5 × 10(-3)  s/mm(2) , FA = 0.36) were estimated. The diffusivities of most metabolites and water were significantly different from each other. Diffusion was found to be anisotropic and the diffusion tensors showed tensor correlation coefficients close to 1 and were hence found to be essentially coaligned. The magnitudes of apparent metabolite diffusivities were largely ordered according to molecular weight, with taurine as the smallest molecule diffusing fastest, both along and across the fiber direction. CONCLUSION Diffusivities, directional dependence of diffusion and fractional anisotropies of (1) H MRS-visible muscle metabolites were presented. It was shown that metabolites share diffusion directionality with water and have similar fractional anisotropies, hinting at similar diffusion barriers. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Data rectification and detection of trend shifts in jet engine path measurements using median filters and fuzzy logic

Filtering methods are explored for removing noise from data while preserving sharp edges that many indicate a trend shift in gas turbine measurements. Linear filters are found to be have problems with removing noise while preserving features in the signal. The nonlinear hybrid median filter is found to accurately reproduce the root signal from noisy data. Simulated faulty data and fault-free gas path measurement data are passed through median filters and health residuals for the data set are created. The health residual is a scalar norm of the gas path measurement deltas and is used to partition the faulty engine from the healthy engine using fuzzy sets. The fuzzy detection system is developed and tested with noisy data and with filtered data. It is found from tests with simulated fault-free and faulty data that fuzzy trend shift detection based on filtered data is very accurate with no false alarms and negligible missed alarms.

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.