Median filter

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

FIR-median hybrid filters with predictive FIR substructures

Abstract: 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 detection of median filtering in digital images

Abstract: In digital image forensics, it is generally accepted that intentional manipulations of the image content are most critical and hence numerous forensic methods focus on the detection of such 'malicious' post-processing. However, it is also beneficial to know as much as possible about the general processing history of an image, including content-preserving operations, since they can affect the reliability of forensic methods in various ways. In this paper, we present a simple yet effective technique to detect median filtering in digital images-a widely used denoising and smoothing operator. As a great variety of forensic methods relies on some kind of a linearity assumption, a detection of non-linear median filtering is of particular interest. The effectiveness of our method is backed with experimental evidence on a large image database.

Harmonic/Percussive Separation Using Median Filtering

Abstract: In this paper, we present a fast, simple and effective method to separate the harmonic and percussive parts of a monaural audio signal. The technique involves the use of median filtering on a spectrogram of the audio signal, with median filtering performed across successive frames to suppress percussive events and enhance harmonic components, while median filtering is also performed across frequency bins to enhance percussive events and supress harmonic components. The two resulting median filtered spectrograms are then used to generate masks which are then applied to the original spectrogram to separate the harmonic and percussive parts of the signal. We illustrate the use of the algorithm in the context of remixing audio material from commercial recordings.

Digital image stabilization with sub-image phase correlation based global motion estimation

Abstract: This paper presents digital image stabilization with sub-image phase correlation based global motion estimation and Kalman filtering based motion correction. Global motion is estimated from the local motions of four sub-images each of which is detected using phase correlation based motion estimation. The global motion vector is decided according to the peak values of sub-image phase correlation surfaces, instead of impartial median filtering. The peak values of sub-image phase correlation surfaces reveal reliable local motion vectors, as poorly matched sub images result in considerably lower peaks in the phase correlation surface due to spread. The utilization of sub-images enables fast implementation of phase correlation based motion estimation. The global motion vectors of image frames are accumulated to obtain global displacement vectors, that are Kalman filtered for stabilization.