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My assignment question is :
"In Lecture 9 Slide No.21 There are Affine Transform based equations. Take an input gray-scale image and apply these transformations one by one. The interpolation used must be bi-cubic."
Now the equations are:
I am not understanding what exactly is meant by this question? I mean should i just apply transformation on an image or what? I am confused
I'm sure your TA could answer here...
Anyway, you have to apply the transformations to a set of coordinates (probably two coordinates per pixel if you want to transform images). Since you will get real values instead of integers (as the pixel grid requires), you have to apply bicubic interpolation to obtain the final values on the destination pixel grid.
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If i have data in NxN grid format (for example see figure) and each cell size is given by (Xmax/N) x (Ymax/N) and data given in each cell is the frequency data of that cell. What is the best way to graphically represent this data in MATLAB such that it is easy to view the frequency for each cell? If I would like to make it like in this example (see colormap), how can I do that what function should I used?
Your choice. Here I put several possibilities:
bar3: if you the points are discrete by meaning
surf or mesh : if the points are continuous by meaning
-imshow or image
in MATLAB 2017b or newer, heatmap
-contour, if you have a sufficiently detailed data
There may be more, please feel free to add them to the post.
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I have plotted the standard deviation of different regions.Can anyone help me to get the conclusions from this boxplot. I just want to conclude the properties of regions. In this figure, eigth object is odd one. What is the significance of whiskers?
How to change the xlabel as region1 ,region2 etc
Coclusions: wide part of your data does not follow a normal distribution. You need something like Violin Plots to see what is rally happening in your data.
Specially for 3-7, as it seems that the number of the outliers is too big.
But remember: Conclusions are obtained from data, not from the plotting option you chose for your data!
about changing the xlabel.... have you tried the function xlabel....?
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I have divided an image into 30 blocks and I want to apply radon transform on each block but I do not know how to do that. I know the radon function in matlab but it is for whole image not for each block.
How may I use the radon function for image blocks?
If you already have the image split into blocks, just call radon() for each block.
You could use blockproc, if you have image toolbox.
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What is The Algorithm For ** Bi-cubic interpolation*?
I am doing this in MATLAB ( i m new to MATLAB). I have already done * Bi-linear interpolation** but i don't know how to do bi-cubic interpolation.
If you need to implement it - read Wiki, link was posted by #robocop
If you need just the result - there is a Curve Fitting Toolbox for Matlab.
Also, I guess, bicubic stands for cubic interpolation for 2D data.
So, you can use interp2 function with method='cubic' to get things done.
Read about it here
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I'm trying to minimize this function (by A):
argmin_A (||L(A)||^2 + a||A-B||^2*)
where:
A is a MxN image L is the Laplacian Operator
||.|| is the usual norm (Frobrenius)
a is a weight parameter
B is a matrix of size (M+2*k)xN
where k is an integer parameter.
(*) indicates that we just consider the pixels in the boundary (we want to preserve in A the pixels in the boundary of B).
Maybe the problem has a trivial solution, but I'm absolutely blocked.
If you need more details, it's (4) equation in this paper.
I will be very grateful for any help provided.
Without looking carefully at that paper, gridfit does essentially that, although it does not employ the boundary conditions you ask for. You could certainly write what you want however, or you could simply apply a weight to the boundary points. This is not a difficult problem, but in order to solve it efficiently, you would want to employ the sparse matrix capabilities of MATLAB.