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.

Median Filter Architecture by Accumulative Parallel Counters

The time to process each of the W/B processing blocks of a median calculation method on a set of N W-bit integers is improved here by a factor of three compared with literature. The parallelism uncovered in blocks containing B-bit slices is exploited by independent accumulative parallel counters so that the median is calculated faster than any known previous method for any N, W values. The improvements to the method are discussed in the context of calculating the median for a moving set of N integers, for which a pipelined architecture is developed. An extra benefit of a smaller area for the architecture is also reported.

A new FIR filter for image restoration

Image filtering techniques have potential applications in biomedical image processing such as image restoration and image enhancement. The potential of traditional filters largely depends on the apriori knowledge about the type of noise corrupting the image. This makes the standard filters to be application specific. For example, the well-known median filter and its variants can remove the salt-and-pepper (or impulse) noise at low noise levels. Each of these methods has its own advantages and disadvantages. In this paper, we have introduced a new finite impulse response (FIR) filter for image restoration where, the filter undergoes a learning procedure. The filter coefficients are adaptively updated based on correlated Hebbian learning. This algorithm exploits the inter pixel correlation in the form of Hebbian learning and hence performs optimal smoothening of the noisy images. The application of the proposed filter on images corrupted with Gaussian noise, results in restorations which are better in quality compared to those restored by average and Wiener filters. The restored image is found to be visually appealing and artifact-free

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.

Noise and outlier removal from jet engine health signals using weighted FIR median hybrid filters

The removal of noise and outliers from measurement signals is a major problem in jet engine health monitoring. Topical measurement signals found in most jet engines include low rotor speed, high rotor speed. fuel flow and exhaust gas temperature. Deviations in these measurements from a baseline 'good' engine are often called measurement deltas and the health signals used for fault detection, isolation, trending and data mining. Linear filters such as the FIR moving average filter and IIR exponential average filter are used in the industry to remove noise and outliers from the jet engine measurement deltas. However, the use of linear filters can lead to loss of critical features in the signal that can contain information about maintenance and repair events that could be used by fault isolation algorithms to determine engine condition or by data mining algorithms to learn valuable patterns in the data, Non-linear filters such as the median and weighted median hybrid filters offer the opportunity to remove noise and gross outliers from signals while preserving features. In this study. a comparison of traditional linear filters popular in the jet engine industry is made with the median filter and the subfilter weighted FIR median hybrid (SWFMH) filter. Results using simulated data with implanted faults shows that the SWFMH filter results in a noise reduction of over 60 per cent compared to only 20 per cent for FIR filters and 30 per cent for IIR filters. Preprocessing jet engine health signals using the SWFMH filter would greatly improve the accuracy of diagnostic systems. (C) 2002 Published by Elsevier Science Ltd.

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,

Fast median calculation method

The ever increasing demand for high image quality requires fast and efficient methods for noise reduction. The best-known order-statistics filter is the median filter. A method is presented to calculate the median on a set of N W-bit integers in W/B time steps. Blocks containing B-bit slices are used to find B-bits of the median; using a novel quantum-like representation allowing the median to be computed in an accelerated manner compared to the best-known method (W time steps). The general method allows a variety of designs to be synthesised systematically. A further novel architecture to calculate the median for a moving set of N integers is also discussed.

Pipelined median architecture

The core processing step of the noise reduction median filter technique is to find the median within a window of integers. A four-step procedure method to compute the running median of the last N W-bit stream of integers showing area and time benefits is proposed. The method slices integers into groups of B-bit using a pipeline of W/B blocks. From the method, an architecture is developed giving a designer the flexibility to exchange area gains for faster frequency of operation, or vice versa, by adjusting N, W and B parameter values. Gains in area of around 40%, or in frequency of operation of around 20%, are clearly observed by FPGA circuit implementations compared to latest methods in the literature.

Automatic road extraction using high resolution satellite images based on Level Set and Mean Shift methods

Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

图像处理在光路自动准直系统中的应用

光路自动准直系统应用于惯性约束聚变的高功率激光装置中的光束自动调整。图像处理是光路自动准直的关键技术之一。针对神光Ⅲ原型装置，结合阈值化、重心法、中值滤波和圆拟合等多种不同的图像处理方法设计了一套合理的准直方案，并且在模拟实验平台上进行了实验验证。实验结果表明，光路自动准直系统能够在15min之内顺利完成光路的自动调整，光束近场调整精度优于近场光斑的±0．5％，光束远场调整精度≤±0．3″，满足了原型装置的总体要求。

Caracterização de imagens de microtomografia de raios X baseada em descritores de textura

A microtomografia computadorizada (computed microtomography - μCT) permite uma análise não destrutiva de amostras, além de possibilitar sua reutilização. A μCT permite também a reconstrução de objetos tridimensionais a partir de suas seções transversais que são obtidas interceptando a amostra através de planos paralelos. Equipamentos de μCT oferecem ao usuário diversas opções de configurações que alteram a qualidade das imagens obtidas afetando, dessa forma, o resultado esperado. Nesta tese foi realizada a caracterização e análise de imagens de μCT geradas pelo microtomógrafo SkyScan1174 Compact Micro-CT. A base desta caracterização é o processamento de imagens. Foram aplicadas técnicas de realce (brilho, saturação, equalização do histograma e filtro de mediana) nas imagens originais gerando novas imagens e em seguida a quantificação de ambos os conjuntos, utilizando descritores de textura (probabilidade máxima, momento de diferença, momento inverso de diferença, entropia e uniformidade). Os resultados mostram que, comparadas às originais, as imagens que passaram por técnicas de realce apresentaram melhoras quando gerados seus modelos tridimensionais.

Interpretação sísmica e análise de atributos - área do levantamento sísmico 3D de siririzinho (Bacia Sergipe-Alagoas, NE do Brasil)

The main objective of the present thesis was the seismic interpretation and seismic attribute analysis of the 3D seismic data from the Siririzinho high, located in the Sergipe Sub-basin (southern portion of Sergipe-Alagoas Basin). This study has enabled a better understanding of the stratigraphy and structure that the Siririzinho high experienced during its development. In a first analysis, we used two types of filters: the dip-steered median filter, was used to remove random noise and increase the lateral continuity of reflections, and fault-enhancement filter was applied to enhance the reflection discontinuities. After this filtering step similarity and curvature attributes were applied in order to identify and enhance the distribution of faults and fractures. The use of attributes and filtering greatly contributed to the identification and enhancement of continuity of faults. Besides the application of typical attributes (similarity and curvature) neural network and fingerprint techniques were also used, which generate meta-attributes, also aiming to highlight the faults; however, the results were not satisfactory. In a subsequent step, well log and seismic data analysis were performed, which allowed the understanding of the distribution and arrangement of sequences that occur in the Siririzinho high, as well as an understanding of how these units are affected by main structures in the region. The Siririzinho high comprises an elongated structure elongated in the NS direction, capped by four seismo-sequences (informally named, from bottom to top, the sequences I to IV, plus the top of the basement). It was possible to recognize the main NS-oriented faults, which especially affect the sequences I and II, and faults oriented NE-SW, that reach the younger sequences, III and IV. Finally, with the interpretation of seismic horizons corresponding to each of these sequences, it was possible to define a better understanding of geometry, deposition and structural relations in the area.

Eliminação de ruído impulsivo em imagens coloridas usando um filtro mediano seletivo e retoque digital

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.

Segmentación de la glotis en imágenes laríngeas usando snakes.

El presente trabajo describe una nueva metodología para la detección automática del espacio glotal de imágenes laríngeas tomadas a partir de 15 vídeos grabados por el servicio ORL del hospital Gregorio Marañón de Madrid con luz estroboscópica. El sistema desarrollado está basado en el modelo de contornos activos (snake). El algoritmo combina en el pre-procesado, algunas técnicas tradicionales (umbralización y filtro de mediana) con técnicas más sofisticadas tales como filtrado anisotrópico. De esta forma, se obtiene una imagen apropiada para el uso de las snakes. El valor escogido para el umbral es del 85% del pico máximo del histograma de la imagen; sobre este valor la información de los píxeles no es relevante. El filtro anisotrópico permite distinguir dos niveles de intensidad, uno es el fondo y el otro es la glotis. La inicialización se basa en obtener el módulo del campo GVF; de esta manera se asegura un proceso automático para la selección del contorno inicial. El rendimiento del algoritmo se valida usando los coeficientes de Pratt y se compara contra una segmentación realizada manualmente y otro método automático basado en la transformada de watershed. SUMMARY: The present work describes a new methodology for the automatic detection of the glottal space from laryngeal images taken from 15 videos recorded by the ENT service of the Gregorio Marañon Hospital in Madrid with videostroboscopic equipment. The system is based on active contour models (snakes). The algorithm combines for the pre-processing, some traditional techniques (thresholding and median filter) with more sophisticated techniques such as anisotropic filtering. In this way, we obtain an appropriate image for the use of snake. The value selected for the threshold is 85% of the maximum peak of the image histogram; over this point the information of the pixels is not relevant. The anisotropic filter permits to distinguish two intensity levels, one is the background and the other one is the glottis. The initialization is based on the obtained magnitude by GVF field; in this manner an automatic process for the initial contour selection will be assured. The performance of the algorithm is tested using the Pratt coefficient and compared against a manual segmentation and another automatic method based on the watershed transformation.