Median filter

About: Median filter is a research topic. Over the lifetime, 12479 publications have been published within this topic receiving 178253 citations.

A new switching-based median filtering scheme and algorithm for removal of high-density salt and pepper noise in images

Abstract: A new switching-based median filtering scheme for restoration of images that are highly corrupted by salt and pepper noise is proposed. An algorithm based on the scheme is developed. The new scheme introduces the concept of substitution of noisy pixels by linear prediction prior to estimation. A novel simplified linear predictor is developed for this purpose. The objective of the scheme and algorithm is the removal of high-density salt and pepper noise in images. The new algorithm shows significantly better image quality with good PSNR, reduced MSE, good edge preservation, and reduced streaking. The good performance is achieved with reduced computational complexity. A comparison of the performance is made with several existing algorithms in terms of visual and quantitative results. The performance of the proposed scheme and algorithm is demonstrated.

Reduction of speckle in digital holography by discrete Fourier filtering.

Abstract: We present a digital signal processing technique that reduces the speckle content in reconstructed digital holograms. The method is based on sequential sampling of the discrete Fourier transform of the reconstructed image field. Speckle reduction is achieved at the expense of a reduced intensity and resolution, but this trade-off is shown to be greatly superior to that imposed by the traditional mean and median filtering techniques. In particular, we show that the speckle can be reduced by half with no loss of resolution (according to standard definitions of both metrics).

Active noise control system for attenuating engine generated noise

Abstract: An active noise control (ANC) system is disclosed for attenuating engine generated noise that contains at least one sinusoidal noise component having an amplitude and frequency that vary with changes in engine rotational speed. The ANC system includes a means for generating at least one generator output signal that contains one or more sinusoidal signal components, where the frequency of each signal component corresponds to the frequency of a respective noise component. A separate control signal having an amplitude that varies with engine rotational speed is generated to correspond with each generator output signal. Each generator output signal is then multiplied by its respective control signal to produce a corresponding filter input signal. Each filter input signal passes to a respective adaptive filter, where it is filtered to produce a corresponding filter output signal according to the adjustable filtering characteristics of the adaptive filter. Noise canceling waves are generated by a noise canceling actuator in response to each filter output signal, and the canceling waves are superimposed with the undesirable noise generated by the engine. The level of residual noise resulting from this superposition is sensed, and an error signal is developed to represent the residual noise level. The filtering characteristics of each adaptive filter are adaptively adjusted based upon the error signal to minimize the residual noise level. In the preferred embodiment, each control signal has its amplitude determined in accordance with a respective predetermined function based upon the sensed engine rotational speed, and each predetermined function is correlative of the amplitude behavior of those noise components corresponding to the signal components contained in the generator output signal that is multiplied by the respective control signal.

Non-linear image filter for filtering noise

Abstract: A system and method for reducing noise using recursive noise level estimation. The system and method for noise reduction substitute a target pixel in a processing window with a weighted average of a plurality of neighboring pixels according to the degree of similarity between the target pixel and the neighboring pixels. The similarity is based on the noise level affecting the image and the local brightness of the processing window. The filter is based on fuzzy logic and filters out noise without smoothing the image's fine details. The filter uses a human visual system (HVS) response to adjust brightness.