Topic
Median filter
About: Median filter is a research topic. Over the lifetime, 12479 publications have been published within this topic receiving 178253 citations.
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Patent•
04 Mar 1991
TL;DR: In this article, three image frames containing an object of interest and background clutter are taken at successive time intervals and stored in memory, and a median filter 16 is used to select a median value from the registered image frames.
Abstract: Three image frames containing an object of interest and background clutter are taken at successive time intervals and stored in memory. The background of images A, B and C are registered preferably using an area correlator 12. A median filter 16 is used to select a median value from the registered image frames. Then, subtractor 18 serves to subtract the median pixel values from one of the image frames. This difference output is then thresholded to provide a binary signal whose pixel values exceeding the threshold levels are generally associated with the position of the moving object.
95 citations
TL;DR: Experimental results show that the proposed method outperforms all the tested state-of-the-art denoising methods with respect to the visual effects and quantitative measure results.
95 citations
TL;DR: Experimental results show that the proposed detector significantly reduces the distortion effects of any impulse noise removal operator even if the operator already has its own noise detector.
Abstract: A new impulse noise detector based on neuro-fuzzy methods is presented. The proposed detector comprises two identical neuro-fuzzy subdetectors combined with a decision maker. The internal parameters of the subdetectors are adaptively adjusted by training. Training of the subdetectors is accomplished by using a simple computer generated artificial image. The detector can be combined with any impulse noise removal operator. The operation of the detector is completely independent of the noise removal operator and it has no influence on the filtering behavior of the operator. Experimental results show that the proposed detector significantly reduces the distortion effects of any impulse noise removal operator even if the operator already has its own noise detector.
95 citations
TL;DR: It is found that the incorporation of conjugate linear filtering improves signal-to-noise ratio by a factor of two in matched filter receivers and the least squares nonlinear receiver for modulations consists of the derived linear-conjugate linear receiver followed by demodulators comparable to those used in practice.
Abstract: Aspects of optimum filtering for complex valued random processes are presented. Ordinary linear filters are complemented with conjugate linear filters. It is found that the incorporation of conjugate linear filtering improves signal-to-noise ratio by a factor of two in matched filter receivers. For optimum least squares filtering the inclusion of conjugate processing reduces mean-square error by a factor as great as two; the improvement depends primarily on the degree of correlation between the real and imaginary parts of the signal process. The analysis utilizes special correlation properties of receiver noise. Also, in the absence of phase lock, conjugate linear processing offers no improvement. Finally, it is observed that in the Gaussian case the least squares nonlinear receiver for modulations consists of the derived linear-conjugate linear receiver followed by demodulators comparable to those used in practice.
95 citations
TL;DR: In this paper, a new noise expression for the class of fixed-point digital filters described by the state equations is formulated, and two methods of its computation are discussed, and the effects of possible structure transformation and state-amplitude scalings are then incorporated in this expression, and results have been analyzed.
Abstract: A new noise expression is formulated for the class of fixed-point digital filters described by the state equations, and two methods of its computation are discussed. The effects of possible structure transformation and state-amplitude scalings are then incorporated in this expression, and the results have been analyzed. In particular, it is shown that the output noise and state amplitudes are inversely proportional, and that an elementary transformation is well suited for a step-by-step generation of a low-noise filter.
94 citations