Standard Median Research Articles

A Robust De-Noising Model for Image Enhancement with Adaptive Median Filtering

This paper presents a robust de-noising model for image enhancement using adaptive median filtering. In this approach image noise is detected with a standard median filter using an adaptive window. Within the window, the original value of the center pixel is changed to a newer that is closer to or same as the standard median. A comparison has been arranged among the proposed method, the standard median (SM) filter and the center weighted median (CWM) filter, which proves the superiority of the proposed filtering method.

임펄스 잡음 제거를 위한 변형된 메디안 필터

As the technology of the digital information age has developed rapidly, lots of research has been done on the digital image processing techniques, such as the image restoration. However, the SM(Standard Median) filter is a typical method of recovering the image which are corrupted by the impulse noise, this method will also reduce the quality of image by generating an error in the edge region. In this paper, in order to restore the corrupted images in the impulse noise environment, a modified median filter algorithm is proposed, which uses the pixels as the center and takes double mask. By using the double mask, we are succeeded in acquiring the excellent performance on noise-canceling, edge preservation, and also in improving the quality of image.

임펄스 잡음제거를 위한 변형된 비선형 필터

영상 신호처리 시스템의 전송 과정에서 여러 가지 원인으로 영상의 열화가 발생하고 있으며 열화의 주된 원인은 잡음에 의한 것으로 알려져 있다. 임펄스 잡음환경에 의해 훼손된 영상의 잡음을 제거하는 대표적인 방법은 SM(standard median filter)가 많이 사용되고 있으며 이 필터는 영상의 에지영역에서 특성이 저하되는 경향이 있다. 따라서 본 논문에서는 비임펄스 신호를 스무딩시키면서 에지를 보존하는 비선형 필터를 제안하였다. 그리고 시뮬레이션을 통해 기존의 방법들과 그 성능을 비교한 결과 영상의 개선 정도를 나타내는 PSNR(peak signal to noise ratio)의 수치가 기존의 방법들보다 우수하였으며, 에지보존특성도 우수하였다. 본 논문에서 제안한 비선형 필터는 영상의 임펄스 잡음제거에 유용하게 응용될 것으로 사료된다. In the transmitting process of image signal processing system, there are several different causes of degradation that have been occurring. The main cause of degradation is attributed to the noise. The most representive method of removing noise of image, which is caused by impulse noise environment, is using the SM(standard median filter). At edge, the filter has a special feature which has a tendency to decrease. As a result, we proposed a nonlinear filter that restores the image considering edge quality in the impulse noise environment. And through the simulation, we compared with the many of the conventional algorithms and the value of the PSNR(peak signal to nise ratio) is better than them and preserve the edge very well. So the nonlinear filter that proposed in this paper is excepted to help improve restoring the images that in impulse noise environment.

Volume reconstruction of freehand three-dimensional ultrasound using median filters

ObjectivesThis paper aims to apply median filters for reducing interpolation error and improving the quality of 3D images in a freehand 3D ultrasound (US) system. Background and motivationFreehand 3D US imaging has been playing an important role in obtaining the entire 3D impression of tissues and organs. Reconstructing a sequence of irregularly located 2D US images (B-scans) into a 3D data set is one of the key procedures for visualization and data analysis. MethodsIn this study, we investigated the feasibility of using median filters for the reconstruction of 3D images in a freehand 3D US system. The B-scans were collected using a 7.5MHz ultrasound probe. Four algorithms including the standard median (SM), Gaussian weighted median (GWM) and two types of distance-weighted median (DWM) filters were proposed to filter noises and compute voxel intensities. Qualitative and quantitative comparisons were made among the results of different methods based on the image set captured in freehand from the forearm of a healthy subject. A leave-one-out approach was used to demonstrate the performance of the median filters for predicting the removed B-scan pixels. ResultsCompared with the voxel nearest-neighbourhood (VNN) and distance-weighted (DW) interpolation methods, the four median filters reduced the interpolation error by 8.0–24.0% and 1.2–21.8%, respectively, when 1/4 to 5 B-scans was removed from the raw B-scan sequence. ConclusionsIn summary, the median filters can improve the quality of volume reconstruction by reducing the interpolation errors and facilitate the following image analyses in clinical applications.

Noise adaptive soft-switching median filter

Existing state-of-the-art switching-based median filters are commonly found to be nonadaptive to noise density variations and prone to misclassifying pixel characteristics at high noise density interference. This reveals the critical need of having a sophisticated switching scheme and an adaptive weighted median filter. We propose a novel switching-based median filter with incorporation of fuzzy-set concept, called the noise adaptive soft-switching median (NASM) filter, to achieve much improved filtering performance in terms of effectiveness in removing impulse noise while preserving signal details and robustness in combating noise density variations. The proposed NASM filter consists of two stages. A soft-switching noise-detection scheme is developed to classify each pixel to be uncorrupted pixel, isolated impulse noise, nonisolated impulse noise or image object's edge pixel. "No filtering" (or identity filter), standard median (SM) filter or our developed fuzzy weighted median (FWM) filter will then be employed according to the respective characteristic type identified. Experimental results show that our NASM filter impressively outperforms other techniques by achieving fairly close performance to that of ideal-switching median filter across a wide range of noise densities, ranging from 10% to 70%

Tri-state median filter for image denoising

In this work, a novel nonlinear filter, called tri-state median (TSM) filter, is proposed for preserving image details while effectively suppressing impulse noise. We incorporate the standard median (SM) filter and the center weighted median (CWM) filter into a noise detection framework to determine whether a pixel is corrupted, before applying filtering unconditionally. Extensive simulation results demonstrate that the proposed filter consistently outperforms other median filters by balancing the tradeoff between noise reduction and detail preservation.

Sinusoidal and pulse responses of FIR-median hybrid filters

Amplitude and phase responses of several types of FIR-median hybrid (FMH) filters are analyzed using sinusoids and rectangular pulses as input signals. It is shown that the linear substructures used in FMH filters limit the overall filter to behave like a lowpass filter, as opposed to the standard median (SM) filter which has some spurious high-gain areas in the otherwise attenuated frequency range. It is shown that the sinewave response of the averaging FMH filter can exceed the response of the FIR subfilter by a factor of >4/ pi . The effect of the phase of the input signal is analyzed. It is found that the phase changes the sinewave responses only at some discrete frequencies. The pulse discrimination responses of several FMH filters are computed. They show that, in noisy conditions, the filter is able to retain pulses longer than the root length and to eliminate those shorter than the root length.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Efficient implementation of one-dimensional recursive median filters

It is shown that in one-dimensional (1-D) recursive median (RM) filtering, the present output is fully determined by the input data in the window and by the most recent output. All other past outputs are shown to be redundant. Based on this result, efficient algorithms and VLSI implementation for 1-D RM filters are presented and are shown to compete favorably with those for standard median (SM) filtering. >

FIR-median hybrid filters with predictive FIR substructures

A class of finite-impulse response (FIR) median hybrid (FMH) filters that contain linear FIR substructures to estimate the current signal value using forward and backward prediction is introduced. The output of the overall filter is the median of the predicted values and the actual signal value in the middle of the filter window. Predictors maximizing the signal-to-noise ratio on signal sections described by an lth-order polynominal are derived. The ramp enhancement filters are shown to attenuate the noise on a ramp signal better than the standard median (SM) filters. The new predictive FMH filters are shown to have root signals which do not exist for the SM filters, e.g. triangular waves. By combining the level and the ramp enhancement FMH filters, a filter is obtained which attenuates noise on constant and ramp signals. The noise attenuation on ramp signals is better than with the SM filter, and the predictive FMH filter has novel and meaningful root structures. The number of arithmetic operations needed to implement the predictive FMH filter grows linearly with the length of the filter. >

On root structures of median and median-type filters

In this correspondence, we analyze the root structures of the standard median (SM) filters, the recursive median (RM) filters, and the FIR median hybrid (FMH) filters. It is shown that these filters have many oscillatory infinitely long root signals. When a section of an oscillatory root is present in a signal, the filter's noise attenuation of the filter is not as good as predicted by statistical measures. We also suggest methods to prevent the possible harmful effect caused by the existence of these roots.

FIR-median hybrid filters

This paper introduces a new generalized class of median-type filters which we call FIR-median hybrid (FMH) filters. The input signal x(n) is filtered with M linear phase FIR filters, and the output of the FMH filter is the median of the outputs of the FIR filters. The statistical properties of the FMH filters are analyzed for input signals with Gaussian, double exponential, and uniform density functions. It is shown that FMH filters have essentially the same statistical properties and same type of root signals as the standard median (SM) filters. FMH filters preserve corner points and ramps and attenuate impulsive-type noise components effectively. An interesting subclass of the FMH filters requiring only one scaling multiplier, two additions, and three compare/swap operations irrespective of the filter length is introduced. In the examples, speed improvement by a factor of 450 is obtained over an otherwise approximately equivalent SM filter.