Image enhancement in frequency domain using Fourier center frequency, Gaussian lowpass filter, Low pass filter, high pass filter. Image restoration using medean filter, weiner filter with noise generator such as Gaussian noise, Salt and Pepper noise
Fast Fourier Transform power point
The rectangular window introduces broadening of any frequency components [`smearing鈥? and sidelobesthat may overlap with other frequency components [`leakage鈥?.
鈥he effect improves as Nincreases
鈥owever, the rectangle window has poor properties and better choices of wncan lead to better spectral properties [less leakage, in particular] 鈥搃.e. instead of just truncating the summation, we can pre-multiply by a suitable window function wnthat has better frequency domain properties.
鈥ore on window design in the filter design section of the course
·Multicarrier Communications: Lie-Liang Yang Wiley | ISBN: 0470722002 | 2009-03-03 ,696 pages Benefiting from both time-domain and frequency-domain signal processing techniques, multi
3D reconstruction, medical image processing from colons, using intel image processing for based class. This source code. Some code missing but I think you can understand it. Development version. This source code is very interesting for learning segmentation and registration from dataset. This code also has some technique about GPU image processing for ray tracing. Also learn many filter apply for transform from spatial domain to frequency domain.
Circular Convolution of two equal-length vectors. Highlights that circular convolution in the time domain is the effectively the same as element-by-element multiplication in the frequency domain.
Spread-spectrum techniques are methods by which electromagnetic energy generated in a particular bandwidth is deliberately spread in the frequency domain, resulting in a signal with a wider bandwidth. These techniques are used for a variety of reasons, including the establishment of secure communications, increasing resistance to natural interference and jamming, and to prevent detec
The 4.0 kbit/s speech codec described in this paper is based on a
Frequency Domain Interpolative (FDI) coding technique, which
belongs to the class of prototype waveform Interpolation (PWI)
coding techniques. The codec also has an integrated voice
activity detector (VAD) and a noise reduction capability. The
input signal is subjected to LPC analysis and the prediction
residual is separated into a slowly evolving waveform (SEW) and
a rapidly evolving waveform (REW) components. The SEW
magnitude component is quantized using a hierarchical
predictive vector quantization approach. The REW magnitude is
quantized using a gain and a sub-band based shape. SEW and
REW phases are derived at the decoder using a phase model,
based on a transmitted measure of voice periodicity. The spectral
(LSP) parameters are quantized using a combination of scalar
and vector quantizers. The 4.0 kbits/s coder has an algorithmic
delay of 60 ms and an estimated floating point complexity of
21.5 MIPS. The performance of this coder has been evaluated
using in-house MOS tests under various conditions such as
background noise. channel errors, self-tandem. and DTX mode
of operation, and has been shown to be statistically equivalent to
ITU-T (3.729 8 kbps codec across all conditions tested.
The single-carrier frequency division multiple access (SC-FDMA)
system is a well-known system that has recently become a preferred
choice for mobile uplink channels. This is attributed to its advantages
such as the low peak-to-average power ratio (PAPR) and the use of
frequency domain equalizers. Low PAPR allows the system to relax
the specifications of linearity in the power amplifier of the mobile
terminal, which reduces cost and power consumption.
Abstract：Noise frequency modulation(FM)jamming。which belongs to blanket jamming。is already become
the main form ofnoise jamming at present。because the wideband was gained by it．Tne spectnlnl ofnoise FM
jamming is analyzed by time domain autocorrelation method in this paper．It’S jamm g peculiarity and幾out—
putting signal’S jamming peculiarity ale explained．At last，these time series models ofnoise FM jalllIIling sig—
nal and幾outputting signal ale built．
