Showing papers on "Median filter published in 1993"

Vector directional filters-a new class of multichannel image processing filters

Abstract: Vector directional filters (VDF) for multichannel image processing are introduced and studied. These filters separate the processing of vector-valued signals into directional processing and magnitude processing. This provides a link between single-channel image processing where only magnitude processing is essentially performed, and multichannel image processing where both the direction and the magnitude of the image vectors play an important role in the resulting (processed) image. VDF find applications in satellite image data processing, color image processing, and multispectral biomedical image processing. Results are presented here for the case of color images, as an important example of multichannel image processing. It is shown that VDF can achieve very good filtering results for various noise source models. >

An adaptive Gaussian filter for noise reduction and edge detection

Abstract: Gaussian filtering has been intensively studied in image processing and computer vision. Using a Gaussian filter for noise suppression, the noise is smoothed out, at the same time the signal is also distorted. The use of a Gaussian filter as pre-processing for edge detection will also give rise to edge position displacement, edges vanishing, and phantom edges. Here, the authors first review various techniques for these problems. They then propose an adaptive Gaussian filtering algorithm in which the filter variance is adapted to both the noise characteristics and the local variance of the signal. >

Morphology-based algorithm for point target detection in infrared backgrounds

Abstract: A morphology-based algorithm has been developed for point target detection in IRST applications. It exhibits comparable detection and false alarm performance to a median filter. The morphology-based algorithm has an efficient computational paradigm based on combinations of simple nonlinear grayscale operations, which makes it ideally suited to real- time, high data rate IRST applications. A detection filter based on morphological background estimation exhibits spatial high-pass characteristics emphasizing target-like peaks in the data and suppressing all other clutter. Example cases are presented which point out the detection performance differences between the morphological and median approaches. Overall performance results were generated in the form of ROC curves for cloud, horizon and sea clutter IRAMMP backgrounds.

Digital video compression system utilizing vector adaptive transform

Abstract: A video compression system comprises a pre-processing section (102), and encoder (106), and post-processing section (114). The pre-processing section (102) employs a median decimation filter (122) which combines median filtering and decimation process. The pre-processing section (102) also employs adaptive temporal filtering and content adaptive noise reduction filtering to provide images with proper smoothness and sharpness to match the encoder characteristics. The encoder (106) employs a two pass look-ahead allocation rate buffer control scheme where the numbers of bits allocated and subsequently generated for each block may differ. In the first pass, the means square error for each block is estimated to determine the number of bits assigned to each block in a frame. In the second pass, the degree of compression is controlled as a function of the total number of bits generated for all the preceding blocks and the sum of the bits allocated to such preceding blocks.

LUM filters: a class of rank-order-based filters for smoothing and sharpening

Abstract: A new class of rank-order-based filters, called lower-upper-middle (LUM) filters, is introduced. The output of these filters is determined by comparing a lower- and an upper-order statistic to the middle sample in the filter window. These filters can be designed for smoothing and sharpening, or outlier rejection. The level of smoothing done by the filter can range from no smoothing to that of the median filter. This flexibility allows the LUM filter to be designed to best balance the tradeoffs between noise smoothing and signal detail preservation. LUM filters for enhancing edge gradients can be designed to be insensitive to low levels of additive noise and to remove impulsive noise. Furthermore, LUM filters do not cause overshoot or undershoot. Some statistical and deterministic properties of the LUM filters are developed, and a number of experimental results are presented to illustrate the performance. These experiments include applications to 1D signals and to images. >

Computing 2-D min, median, and max filters

Abstract: Fast algorithms for computing min, median, max, or any other order statistic filter transforms are described. The algorithms take constant time per pixel to compute min or max filters and polylog time per pixel, in the size of the filter, to compute the median filter. A logarithmic time per pixel lower bound for the computation of the median filter is shown. >

Stop-sign recognition based on color/shape processing

Abstract: This paper presents a robust vision-based stop-sign reconition technique based on sequential processing of color and shape. The primary red-green-blue color coordinate system is first transformed into the saturation-hue-brightness color coordinate system. This color coordinate system allows the red color area of a stop sign to be bounded under various brightness conditions caused by weather, sun angle, or shadows. A combination of a median filter, a morphological filter, Sobel edge operator, and Hough transform is then employed to obtain the boundary contour. It is demonstrated that the parameters of eight straight lines representing the octagonal sides are sufficient for this purpose. Experimental results indicate that stop signs are successfully distinguished from other traffic sighs and background clutter.

Filter to reduce speckle artifact in ultrasound imaging

Abstract: A method for reducing speckle artifact in an ultrasound image using a two-dimensional median filter having a diamond-shaped five-point kernel. The entire pixel image data is passed through the filter in a manner such that the center point of the kernel is effectively stepped down each range vector in sequence. The magnitudes of the pixel data at each of the five points in the kernel are compared and the value which has the middle magnitude is adopted as a new pixel value, which is substituted for the old pixel value at the center point. After a new filtered vector has been formed from the new pixel values produced at successive center points by stepping down one acoustic vector, the kernel is shifted by one vector and stepped down range again. This process continues through the entire set of vectors until a new set of filtered vectors is formed. This filter will remove speckle holes on the order of one pixel in size while preserving good edge definition.

A new algorithm for order statistic and sorting

Abstract: An algorithm for rank filtering and stack filtering is presented. This algorithm is simple and results in fast and easy implementations. Various implementations of the algorithm are described, and the H-tree design is shown to be most area efficient. Also introduced is a modification of the filtering algorithm that results in better implement sorting. >

Noise removal from color images

Abstract: The noise effects in color images are studied from the human perception and machine perception point of view. Three justifiable observations are made to illustrate problems related to individual color signal processing. To minimize the noise effects, two solutions are studied: One is a ‘rental scheme’ and the other is a vector signal processing technique. The ‘rental scheme’ adopts filters originally developed for grey scale images to color images. A set of heuristic criteria is defined to reconstruct an output with minimum artifacts. The vector signal processing technique utilizes a median vector filter based on the well developed median filter for grey scale images. Since the output of the filter does not have the same physical meaning as the median defined in one-dimensional space, the search of a vector median is considered as a minimum problem. The output is guaranteed to be one of the inputs. Both approaches are shown to be very effective in removing speckle noise. Results from real and synthetic images are obtained and compared.

Locally monotonic regression

Abstract: The concept of local monotonicity appears in the study of the set of root signals of the median filter and provides a measure of the smoothness of the signal. The median filter is a suboptimal smoother under this measure of smoothness, since a filter pass does necessarily yield a locally monotonic output; even if a locally monotonic output does result, there is no guarantee that it will possess other desirable properties such as optimal similarity to the original signal. Locally monotonic regression is a technique for the optimal smoothing of finite-length discrete real signals under such a criterion. A theoretical framework in which the existence of locally monotonic regression is proved and algorithms for their computation are given. Regression is considered as an approximation problem in R/sub n/, the criterion of approximation is derived from a semimetric, and the approximating set is the collection of signals sharing the property of being locally monotonic. >

A new adaptive separable median filter for removing blocking effects

Abstract: A novel adaptive separable median filter as a postfilter is presented for removing the blocking effects which generally originate from lower-bit-rate image transmission. This filter adaptively transforms from a traditional median filter to a low-pass filter progressively when the filter is close to the position of blocking effects. Simulation results demonstrate that this filter is extremely useful not only in removing the blocking effects, but also in maintaining the main advantages of the median filter such as edge preservation and noise reduction. >

Processing Ground Penetrating Radar Data To Improve Resolution Of Near-Surface Targets

Abstract: Although unprocessed ground penetrating radar (GPR) data are capable of producing detailed images of the shallow subsurface, these images may be difficult to interpret reliably. Here, we investigate characteristics of GPR signals and various techniques to enhance GPR images. The processing steps are tested on GPR datasets acquired at a well-controlled site where two concrete blocks, simulating archaeological structures, are buried less than two meters from the surface. Short range GPR signals often possess a low-frequency component (commonly referred to as a ttwowtt) that causes amplitude distortion along an individual trace. Characteristics of this noise are considered in light of its physical cause, i.e., saturation of the receiver electronics. Three filter techniques were tested to remove the wow: (i) residual mean filtering, (ii) bandpass filtering, and (iii) residual median filtering. We found that the residual median filter performed best. Additional signal processing steps included static corrections, normal moveout (NMO) corrections, migration and eigen filtering. Static corrections compensate for drift of the time-zero sample that occurs during acquisition. NM0 corrections remove spatial distortion due to source-receiver offset. Migration focuses diffracted energy and corrects dipping reflectors thereby improving spatial resolution. Eigen filtering removes the coherent direct arrivals to improve the detection of near-surface features. Application of these processing techniques significantly improves the quality of the GPR images from the test site, both in terms of the positioning of events and resolving capability. By testing various enhancement techniques on data collected at wellcontrolled sites, a better understanding is gained of their relative benefits and the ultimate capabilities of GPR as a shallow exploration tool.

Noise eliminative circuit employing a coring circuit

Abstract: A noise eliminative circuit for eliminating noise components contained in an input image signal in which a high-frequency noise component is eliminated through a coring circuit, and a low-frequency noise component is selectively eliminated by horizontal and vertical correlation, without a damage to the input image signal. A coring circuit is employed for a horizontal high-frequency component of an image signal to remove a minute noise component, and an impulse noise elimination method is applied to a remaining component of the image signal to eliminate the noise component which is also removed in accordance with a user's selection of the high-frequency band.

Performance characteristics of the median LMS adaptive filter

Abstract: The median least-mean-square (MLMS) adaptive filter alleviates the problem of degradation of performance when inputs are corrupted by impulsive noise by protecting the filter coefficients from the impact of the impulses. MLMS is obtained from the least mean square (LMS) by applying a median operation to the raw gradient estimates of the mean-squared-error performance surface. The algorithm is analyzed for the class of independent and identically distributed inputs, establishing exponential convergence. The rate of convergence is shown to depend on order statistics of the input but shows little dependence on characteristics of the impulsive interference. Analysis of the steady-state performance indicates a significantly improved performance for MLMS compared to LMS. Analytic predictions for both convergence and steady-state behavior are supported by simulations. >

A comparison of adaptive filters for edge-preserving smoothing of speckle noise

Abstract: The authors present the results of an extensive study investigating the applicability of different existing nonlinear adaptive filtering methods, as well as a new speckle-model based quadratic Volterra filter (QVF), to solve the problem of smoothing speckle noise in digital images while preserving important edge information. The QVF consists of a linear part, mainly responsible for noise smoothing, and a quadratic part for filtering near edges. This filtering strategy allows for consideration of the local correlation of speckle noise. The three best overall filters were found to be the Lee multiplicative filter, the Frost filter and the quadratic Volterra filter. The QVF provides promising results in both noise smoothing and edge preservation. >

Filtering random noise via data compression

Abstract: A general technique is suggested for reducing random noise from signals using data compression in conjunction with the principle of Occam's Razor. Not only are classical spectral filters realisable as a particular instance of the technique, but more powerful nonlinear filters fall within its scope. >

An analog circuit technique for finding the median

Abstract: A novel analog technique for finding the median of an odd number of inputs is presented. It is shown that simple analog circuits can be used to find the median. Their compactness allows their use in parallel systems, such as pixel plane processing, yielding enormously effective computation rates. In addition, their analog nature allows them to be easily incorporated into systems where digital median filters are impractical, such as high-speed communications equipment. More generally, the technique described can be used to implement a large class of nonlinear filters based on rank order. A three-input median circuit, implemented in a 2-/spl mu/m CMOS process, demonstrates the effectiveness of the technique.

Clustering filter method for noise filtering, scale-space filtering and image processing

Abstract: A method is provided for image processing to remove noise and improve smoothing of nonimpulsive noise while preserving major identifying edges of the image, all of which are accomplished corresponding to a prescribed scale of interest. The method achieves nonlinear cluster filtering relying upon a maximum entropy principle. A single scale parameter governs filtering by dictating the spatial extent of neighboring data used for clustering. This, together with the signal characteristic (e.g., variation in gray scale) determines the scale parameter in the output space. The described method is unsupervised and data driven.

X-ray examination apparatus and means for noise reduction for use in an x-ray examination apparatus

Abstract: Noise reduction for use in an x-ray examination apparatus is provided for performing weighted temporally averaging in dependence on an amount of motion in parts of successive x-ray images. Further noise reduction is performed by combining temporal averaging with spatial filtering and motion detection. This reduces both noise breakthrough and the occurrence of trailers. In particular, noise breakthrough is appropriately reduced by hi-temporal filtering. Threshold-values for discriminating between noise and motion are computed on the basis of images generated by the x-ray detector.

High temporal resolution velocity estimates from a wind profiler

Abstract: Existing techniques for rejecting spurious data in single-cycle wind profiles employ a consensus average method to several profiles. This technique sometimes fails and also severely limits temporal resolution. The authors find by first applying a median filter to three successive single-cycle (3 min) spectral data and then guiding the velocity calculation by a first guess, it is possible to extract high-quality wind profiles at 3-min intervals. For support to launch operations, it is critical the wind-profile data be correct. The authors introduce an interactive quality control methodology in which the median spectral data are overlaid with the computed velocity profile. Two test cases are presented.

70-MHz 2- mu m CMOS bit-level systolic array median filter

Abstract: An algorithm for VLSI median filtering of one-dimensional signals of complexity linearly dependent on the filter window length is described. The algorithm is implemented as a bit-level systolic array (BLSA), in order to achieve high performance. A single-chip median filter characterized by a window length of 25 8-b samples, and by operation on three interleaved independent sequences for a total of 75 samples, is presented as a demonstration of the concept. The throughput relevant to one sequence is 1/3 for this chip, whereas the theoretical maximum allowed by the algorithm is 1/2. Prototypes designed with a 2- mu m CMOS technology have been successfully tested at a clock frequency over 70 MHz. >

Video images decoder architecture for implementing a 40 ms processing algorithm in high definition televisions

Abstract: A video image decoder architecture for implementing a processing algorithm in the 40-ms mode on high-resolution TV sets, of a kind adapted to handle TV signals being received on respective transmission channels (J,L), which comprises a video signal demultiplexer receiving the transmission channels (J,L); and respective processing blocks for separately handling the signals from each of the channels (J,L). Each processing block includes a video image format converter, a local memory connected to an output of the converter, and at least one median filter and one systolic filter cascade connected after the memory for restoring, by interpolation, signal samples related to successive lines of the video image. A summing node adds the outputs from each processing block so as to obtain a time mean between restored samples of the channels (J,L). This architecture drastically reduces the number of memories required for processing the restored algorithm, as well as reducing overall silicon area requirements for the system. Accordingly, the whole 40-millisecond processing portion may be integrated into a single chip.

Decoding using a linear metric and interference estimation

Abstract: In a decoding system according to the invention, a digital signal received from an AWGN channel interfered by pulse interferences is so decoded (8) that the AGC control signal (10) of the RF/IF circuits of the reception is produced by median filtering (21) for the essential removal of the effect of pulse interferences, and that the interference is measured using a linear metric, whereby an external interference estimation circuit (30) is preferred.

A real-time 2-D median based filter for video signals

Abstract: A 2-D, multishell median-based filter for real-time video signal processing is presented. The device is able to remove impulse and missing line noise in real-time without blurring sharp video images. A prototype using 75 standard transistor-transistor logic (TTL) chips has been realized on one single speedwire prototype board of size 17*30 cm/sup 2/ and its structure is suitable for VLSI implementation. The statistical performance of the nonlinear filter has been investigated and compared with that of standard 2-D median filters. It is shown that the filter has characteristics superior to those of its median-based counterparts while the hardware implementation is much simpler. >