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The EDIUpsizer was designed to be a resampling filter that upsizes an image by a factor of two both horizontally and vertically using NEDI (new-edge directed interpolation).
Download •
Download •
EDIUpsizer With Registration Code
The YFCC is a classifier, which implements the five-class system, as described in this document. Each of the five categories contains an explicit class name. The five classes of the YFCC are:
I:
1.
P:
2.
D:
3.
S:
4.
O:
5.
All the names correspond to the IPRM (Informal Panoramic and
Rovin Mosaic) class definitions in this document.
ECIQ Labels are interpreted as follows:
I: the entire image is contained in this category.
P: the complete image is significantly darker than the entire image, but the image is not totally black.
D: the entire image is darker than any part of the image, possibly with a black/white boundary.
S: the entire image is similar to a digital panorama, but is not processed for IPRM and normalization.
O: the complete image is similar to a digital panorama, but is processed for IPRM and normalization.
.3 Objectives and Key Features
The YFCC offers high-quality results when applied on many real
images and different degrees of noise. The YFCC is one of the
most detailed algorithms for processing sub-patch level image
sets.
If the main goal of a document or research project is to obtain
good quality image sets, the YFCC is the right algorithm. The
five-class system can be used to identify the best quality
images for the main goal of the document or research project.
Furthermore, the five classes offer the possibility of obtaining
very good results (case S and O) when combined with a selection
algorithm. See Sect. 6.2.1 for details.
The YFCC performs at the sub-patch level. For most documents
and research projects, small image subsets must be considered,
because the complete image may be too large for the user
who is looking at it. Similarly, larger image sizes (where
a factor of two must be used) are common for desktop publishing
applications. Such reasons make it necessary to divide the
complete image into sub-regions, where it is necessary to
evaluate the quality of the results.
The YFCC
EDIUpsizer License Key Full
(lengthwise-dyadic
upsizing filter with
dual-edge direction)
Source: [Matsuda,I.N. and Hatori, N., 2018-01-27]
But I want to upsizing image like:
Source:
A:
You can just use interpolation along the $x-$ and $y-$ axis. This will be done using bilinear interpolation. Refer to the MATLAB documentation for further information on the function INTERP2. If you don’t want to interpolate along the $y-$ axis, you can just select that axis to interpolate by setting it to false.
% Create an image of size $320\times 320$
% This first uses FINDCOUNT to extract the number of pixels in the image.
imageSize = [320,320];
figure;
for i=1:1:imageSize(1)
x = linspace(1,imageSize(1),i);
y = linspace(1,imageSize(2),i);
figure;
image = img(x,y);
% Interpolate along the $x-$ and $y-$ axis
x_interpolated = interp2(x, [0, 1], y, [0, 1], ‘bilinear’, false);
y_interpolated = interp2(x, [0, 1], y, [0, 1], ‘bilinear’, false);
figure;
imshow(image);
title(sprintf(‘i = %d’,i));
drawnow;
end
This will give you
Now, you can scale the $x-$ and $y-$ axis by using $1/2$.
y_interpolated = interp2(x, [0, 1], y, [0, 1], ‘bilinear’, false);
x_interpolated = interp2(x, [0, 1], y, [0, 1], ‘bilinear’, false);
figure;
for i=1:1:imageSize(1)
x = linspace(1,imageSize(1),
7ef3115324
EDIUpsizer License Keygen Download PC/Windows
========
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System Requirements:
Minimum:
OS: Win7/8, Mac OS X 10.5.x
Processor: Dual core with at least 2.4 GHz, more can run
Memory: 1 GB RAM
Graphics: Direct3D 9-capable with DX9 driver
DirectX: Version 9.0c
Storage: 3 GB free space
Additional Notes:
It is recommended to use an updated graphics driver
Recommended:
OS: Win7/8, Mac OS X 10.6.x
Processor
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