smoothing filter

smoothing filter

[′smüth·iŋ ‚fil·tər]
(electronics)
Mentioned in ?
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Each drive microsteps to 25,000 steps/rev with a 1.8[degrees] step motor (1/125 step) even when command pulses are low resolution-thanks to the proprietary step smoothing filter. Users can set up drive parameters- including motor selection, current, and step resolution-using dip or rotary switches.
Figure 2 shows the actual motor speed and Kalman Filter and smoothing filter estimated speed and their zoomed response.
Smoothing Filter. The velocity traces of both the head and eye contain small ripples, which possibly influence on the gain calculation and saccade detection.
Bi Lateral filtering is a simple, non-linear, edge preserving and noise reducing smoothing filter for images.
As shown in Figure 3, the collected geomagnetic field intensity data, even in the same sampling point, for a period of time, the data will be 2uT jitter, so we use the median filter and the original data Smoothing filter. The filtered data can improve the match rate when the original data is retained, which is the main feature of the original data.
Bilateral filtering [1] is the most intuitive nonlinear smoothing filter, although it suffers from the gradient inversion effect, which uses a histogram-based approximation to calculate the weight, and it is computationally complex.
Caption: FIGURE 4: Comparison of different image smoothing filter and their corresponding segmentation results.
The expression of the smoothing filter as defined in DO-253C [7] is
In order to reduce as much noise as possible without impairing loss in the original signal information due to elimination of important frequencies a use of a classic filter may be insufficient, and that's because it requires a polynomial smoothing filter such as the Savitzky-Golay filter.
Filters that are commonly used on SPECT imaging are the Ramp filter, a high pass filter eliminating the star artifact and blurring, the Hanning filter, a low pass smoothing filter, the Hamming filter, also a low pass smoothing filter having a different amplitude at the cutoff frequency, the Butterworth filter, which both smoothers noise and preserves the image resolution, the Parzen filter, the most smoothing low pass filter, and the Shepp-Logan filter, which is the least smoothing but has the highest resolution [4].
The visual experiments illustrate that the proposed FHD algorithm achieves the maximum PSNR value over Gaussian smoothing filter and Wiener filter, although the PSNR rate is slightly higher than Gaussian filter and Wiener filter.
The S9 filter (a smoothing filter) acts uniformly, calculating an average value for a group of pixels, and redistributing the density mean among the pixels, resulting in an image that has more uniform gray tones and is less granular.