## Forums Search for: Deconvolution

## deconvolution problem

inHi, I have a problem with vector deconvolution. This is what I do in Matlab: > > vect1=[1 2 3 4 5 6 7 8 9]; > > vect2=[1 2 3 4 0 0 0 0 0...

Hi, I have a problem with vector deconvolution. This is what I do in Matlab: > > vect1=[1 2 3 4 5 6 7 8 9]; > > vect2=[1 2 3 4 0 0 0 0 0 0 0 0 0 0]; %I want to find w with conv(w,vect1)=vect2 > > Lx=length(vect2)-length(vect1)+1; > > Lx2=pow2(nextpow2(Lx)); > > VECT1=fft(vect1,Lx2); > > VECT2=fft(vect2,Lx2); > > W=VECT2 ./ VECT1; > > w=real(ifft(W,Lx2)); > > w=w(1:1:Lx); > > w=w/max(abs(w));

## deconvolution problem

inHi, I have a problem with vector deconvolution. This is what I do in Matlab: > > vect1=[1 2 3 4 5 6 7 8 9]; > > vect2=[1 2 3 4 0 0 0 0 0...

Hi, I have a problem with vector deconvolution. This is what I do in Matlab: > > vect1=[1 2 3 4 5 6 7 8 9]; > > vect2=[1 2 3 4 0 0 0 0 0 0 0 0 0 0]; %I want to find w with conv(w,vect1)=vect2 > > Lx=length(vect2)-length(vect1)+1; > > Lx2=pow2(nextpow2(Lx)); > > VECT1=fft(vect1,Lx2); > > VECT2=fft(vect2,Lx2); > > W=VECT2 ./ VECT1; > > w=real(ifft(W,Lx2)); > > w=w(1:1:Lx); > > w=w/max(abs(w));

## Design of a deconvolution filter

inHi, I am really new to this so bear with me. I got a homework assignment for a course called analytical topics and I was wondering if anybody...

Hi, I am really new to this so bear with me. I got a homework assignment for a course called analytical topics and I was wondering if anybody could help me figure it out. I don't need a complete answer but just some pointers of where to begin with this problem and how to proceed. Thank you very much for any information. The setup is as follows: I am given an fir filter: y(k)=sum[u(k-i)h(k)] ...

## Deconvolution

inIf I have a random signal u(k) and a (known) transfer function H then y(k)=Hu(k) and if I know H and H is minimum phase then I ca neasily find...

If I have a random signal u(k) and a (known) transfer function H then y(k)=Hu(k) and if I know H and H is minimum phase then I ca neasily find u(k). Suppose H is nonminimum phase eg y(k)=u(k)-2u(k-1) how to get at u(k)? Can I run time backwards in some way so the H is stable in reverse time? hardy

## deconvolution in time?

inHello! I have a output signal y(k) and a plant P(z). The signal y(k) contains some noise and I know the PSD of the noise. But lets assume that...

Hello! I have a output signal y(k) and a plant P(z). The signal y(k) contains some noise and I know the PSD of the noise. But lets assume that for now that the noise is qhite and the system looks like this: Y(z)=U(z)P(z)+E(z) u(k) y(k) ----------> [P(z)]--> [+]---> | e(k) | -------| I want to restore the sig

## Prewhitening....how to explain?

inHi All, Is there a book or source that explains what prewhitening is, in relatively simple terms? Or would any of you like to explain it to...

Hi All, Is there a book or source that explains what prewhitening is, in relatively simple terms? Or would any of you like to explain it to me, please? I have a blood flow signal and I want to prewhiten it and then do some blind deconvolution on it to see what happens. As the prewhitener it has been suggested to use a predictor as the signals I have are quite short. (Some form of stocha...

## Deconvolution by Fourier method

inIn order to convolve two functions 'a' and 'b', we can take their Fourier Transform(FT) and multiply them in Fourier domain i.e. C= FT(a) *...

In order to convolve two functions 'a' and 'b', we can take their Fourier Transform(FT) and multiply them in Fourier domain i.e. C= FT(a) * FT(b) c = IFT(C) and then Inverse Ft(IFT) of 'C' gives us the convolution of 'a' and 'b'. Now if we want to deconvolve 'a' from 'c' to get 'b' we can do B = FT(c)/FT(a) b = IFT(B) Now if 'a' is a square wave i face the problem of 'DIVIDE by ZERO', a...

## Deconvolution of two gamma variates

inHi! I'm busy with a project to determine cerebral blood flow using MRI. At two places in the brain the concentration of a contrast solution...

Hi! I'm busy with a project to determine cerebral blood flow using MRI. At two places in the brain the concentration of a contrast solution is measured every 1 second (or so.) The points are then fitted to a gamma variate of the form: f(t) = a (t-to)^b exp[ -(t-t0)/c ] for t=> t0 f(t) = 0 t

## how to minimize ringing

inHello, I am trying to restore a one dimentional signal using wiener deconvolution with a PSF. Because it's important for me to restore sharpness,...

Hello, I am trying to restore a one dimentional signal using wiener deconvolution with a PSF. Because it's important for me to restore sharpness, but more important, the shape at the transient edges- the ringing is getting in my way. I understand that ringing to some extent is unavoidable, but how can I miminize it? Thank you, Keren

## "Repairing" an out-of- focus picture

inHi, My question might be simplistic as neither optics nor image processing is my field. Firstly, I was wondering if it is possible to...

Hi, My question might be simplistic as neither optics nor image processing is my field. Firstly, I was wondering if it is possible to compensate for a picture taken by an out-of-focus digital camera by doing a 2D deconvolution on it (MMSE filtering or something like that), in order to recover the in-focus picture Secondly, can the optical transfer function between a properly focused pi...

## Deconvolution problem

inHi guys, I have a theoretical relationship that variable z = convolution(x, y ). I now have vectors of z and x and I am trying to deconvolute...

Hi guys, I have a theoretical relationship that variable z = convolution(x, y ). I now have vectors of z and x and I am trying to deconvolute them to get vector y. I tried to to FFT to solve for y. The problem is that I also got some oscillation in the y vector while there should be none. The shape of the vectors z and x all look like bell shape and they look pretty smooth. They are close to z...

## Problem with image deconvolution

inHullo All, I recently posted to this group on this question but I never saw it appear, so please excuse my posting again. I have two...

Hullo All, I recently posted to this group on this question but I never saw it appear, so please excuse my posting again. I have two overlapping images (apprx. 30% overlap) which are part of a series to be stitched into a panorama. One image is blurred by motion blur, the other is sharp. As I effectively have the blurred and the 'latent' images it seemed like there was a fair chance I could...

## Lytro

inAfter seeing discussino of the Lytro light-field camera, the first thought I had was that DSP would be pretty important in making it work. Yet I...

After seeing discussino of the Lytro light-field camera, the first thought I had was that DSP would be pretty important in making it work. Yet I don't remember seeing any discussion of it. The article describing the technology is: http://graphics.stanford.edu/papers/lfcamera/lfcamera-150dpi.pdf it would seem to me that deconvolution would be related to the technology, though so far, (a...

## Re: deconvolution in time?

inGordon Sande wrote: > On 2005-11-08 09:41:43 -0400, abariska@student.ethz.ch said: .=2E. > There are two common usages of adjoint. > > ...

Gordon Sande wrote: > On 2005-11-08 09:41:43 -0400, abariska@student.ethz.ch said: .=2E. > There are two common usages of adjoint. > > One is in matrix theory where it is the transpose of the matrix of cofact= ors > as one would find near the definition of determinants and how to solve > equations using determinants. I just looked through all my pure linear algebra books (Lang, J=E4nich

## Deconvolution question

inSuppose I have an acoustic guitar with a (relatively good-sounding) peizo pickup (a K&K, for those interested). I can mic the guitar and...

Suppose I have an acoustic guitar with a (relatively good-sounding) peizo pickup (a K&K, for those interested). I can mic the guitar and record the peizo simultaneously. But when I deconvolve the miked signal against the peizo, the resulting convolution signature isn't very coherent. Most convolution signatures of this nature have a "spike" where the dominant bucket is - this has just a ...

## vibroseis deconvolution without the reference sweep

inI have a vibroseis dataset which has been collected in the field. To my knowledge, the recorded signal s'[t] is the convolution of the...

I have a vibroseis dataset which has been collected in the field. To my knowledge, the recorded signal s'[t] is the convolution of the original sweep s[t] and the reflection response r[t] of the layered earth. Thus, the relationship is expressed in its simplest form as s'[t] = s[t]*r[t], neglecting the effects of earth attenuation and noise. However, I do not have the reference sweep s[t] since...

## deconvolution using known set of filters

ini have lot of filters impulse responses and signal 'x' that i got by convolving original signal 's' with one of the filter...

i have lot of filters impulse responses and signal 'x' that i got by convolving original signal 's' with one of the filter impulse response.Also,the signal 'x' contains noise. Now i want to recover the original signal 's'. 1)Which techniques are most feasible and effective to solve this problem 2)which technique is more real time

## Discrete Deconvolution

inHello, all. I have a dilemma. I'm analyzing some time signals for periodicities, and I was wondering about a seemingly basic method of doing...

Hello, all. I have a dilemma. I'm analyzing some time signals for periodicities, and I was wondering about a seemingly basic method of doing it. I hope you'll forgive my ignorance, as my specialty is physics and not signal processing :P So, we have a time-series that is the product of a source signal and a window function : c(t_i) = w(t_i)s(t_i) where t_i represents the i_th time...

## Which algorithm would you choose?

inSay you have two signals, x and y, where y is the output of an unknown FIR filter. The only thing which is "known" about the FIR filter is that...

Say you have two signals, x and y, where y is the output of an unknown FIR filter. The only thing which is "known" about the FIR filter is that it has N filter coefficients. The above relates to acoustic echo cancellation for speech signals sampled at 8kHz. I guess you can call it a channel estimation problem? Or a deconvolution problem? I don't know.... Anyways....As a pre-liminary expe...

## Mixed phase deconvolution

inHello all DSP gurus, I am struggling with some (seismic) DSP theory and need some help! In seismic the convolutional model states that the...

Hello all DSP gurus, I am struggling with some (seismic) DSP theory and need some help! In seismic the convolutional model states that the observed signal as a function of time, st (seismic trace), equals the convolution between the seismic shot signal, s, and the earth response function, e: st=s*e. Given a known st and s I want to calculate the unknown e. We introduce a pulse shaping fi...