Median filter

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

Mediated morphological filters

Abstract: This paper presents new morphological operators based on a special combination of median filtering and classical gray-scale morphological operators. The newly introduced operators demonstrate a superb performance compared with classical ones and even weighted morphological operators (Sedaaghi and Wu (1998)) introduced by the author, for signals/images buried in speckle, salt and pepper, and Gaussian noise. Their efficiency is comparable with convolutional filtering for speckle and Gaussian noise removal, where classical morphological operators fail to be applicable. The proposed algorithms have been applied for off-line biomedical signal/image processing successfully.

A Nonlinear Filter to Remove Impulse Noise from Meteorological Data

Abstract: Nonlinear median filters were modified to use threshold logic and used to remove impulse noise (spikes) from a set of meteorological data. The impulse noise in the dataset, which originated in the communications section of the Portable Automated Mesonet, could be characterized as random bit noise. Most of the pulses had a duration of one time interval, which in this case was one minute. The filters were effective irrespective of the frequency of occurrence and of the amplitude of the noise spikes. Pulses were removed even when the frequency of occurrence rose to every other data point as was observed in several short intervals. The amplitude of pulses removed ranged over three orders of magnitude.

A Study on the Method of Image Pre-processing for Recognition of Crop Diseases

Abstract: Regarding the cucumber powdery mildew, speckle and downy mildew as examples, the method of image pre-processing for recognizing crop diseases was studied. This paper compared the effect of two filters—Simple filter and Median filter, and at last we chose median filter to wipe out the disturbance of noise effectively, and two-apex method was applied to separate the disease images from the background. Disease spots were separated through performing image edge detection and Snake model, and the latter got more desired result. Thus the image pre-processing made a good foundation for following effective characteristic parameters for the disease diagnoses and setting up pattern recognition system.

Image Registration Error Variance as a Measure of Overlay Quality

Abstract: When one image (the sigal) is to be registered with a second image (the signal plus noise) of the same scene, one would like to know the accuracy possible for this registration. This paper derives an estimate of the variance of the registration error that can be expected via two approaches. The solution in each instance is found to be a function of the effective bandwidth of the signal and the noise, and the signal-to-noise ratio. Application of these results to LANDSAT-1 data indicates that for most cases registration variances will be significantly less than the diameter of one picture element.

Noise reduction method, apparatus, and program for digital image processing

Abstract: A method of processing a digital image channel to remove noise, includes the steps of: identifying a pixel of interest; calculating a noise reduced pixel value from a single weighted average of the pixels in a sparsely sampled local region including the pixel of interest; replacing the original value of the pixel of interest with the noise reduced pixel value; and repeating these operations for all of the pixels in the digital image channel.