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# image restoration，CT scan，closed curve，

By : marthy
Date : November 22 2020, 03:01 PM
This might help you The technique you are looking for is called dilation. There is an example in the opencv library erosion and dilation
code :

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## How to draw closed spline 3D (closed curve 3d) through unordered list of points3D. How to arrange points3D?

By : megatcorleone
Date : March 29 2020, 07:55 AM
wish of those help It sounds like you're looking for the Concave Hull of the data set.
Unfortunately, I don't know of any pre-canned algorithms, but the link references a paper that another developer was starting from, as well as some sample code, so maybe that'll help you in the right direction.

## Image noise removal is part of image enhancement or image restoration?

By : Spviit
Date : March 29 2020, 07:55 AM
like below fixes the issue Well there is the wikipedia page http://en.wikipedia.org/wiki/Image_restoration
It says that

## Closed Bezier curve

Date : March 29 2020, 07:55 AM
seems to work fine Simply use an additional segment that connects the last endpoint to the first (ex: duplicating the first control point).
A single bezier spline segment, whether it's cubic or quadratic or quartic, can't represent that kind of closed shape. Yet multiple segments can.

## Hilbert-Peano curve to scan image of arbitrary size

By : thanh nguyen
Date : March 29 2020, 07:55 AM
I think the issue was by ths following , I finally choose, as suggested by Betterdev as adaptive curves are not that straigthforward [1], to compute a bigger curve and then get rid of coordinates which are outside my image shape:
code :
``````# compute the needed order
order = np.max(np.ceil([np.log2(M), np.log2(N)]))
# Hilbert curve to scan a 2^order * 2^order image
x, y = hilbert_peano(order)
mat = np.zeros((2**order, 2**order))
# curve as a 2D array
mat[x, y] = np.arange(0, x.size, dtype=np.uint)
# clip the curve to the image shape
mat = mat[:M, :N]
# compute new indices (from 0 to M*N)
I = np.argsort(mat.flat)
x_new, y_new = np.meshgrid(np.arange(0, N, dtype=np.uint), np.arange(0, M, dtype=np.uint))
# apply the new order to the grid
x_new = x_new.flat[I]
y_new = y_new.flat[I]
``````

## Fitting a closed curve then drawing equidistant points from that curve

By : Zander
Date : March 29 2020, 07:55 AM
may help you . Perhaps this gets you started. The xsplinefunction allows for creating a closed spline - although I am unsure how to control the number of interpolated points. This answer demonstrates the use of the xspline function.