Image denoising thesis
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Effective Quadtree Plus Binary Tree Block Partition Decision for Future Video Coding [PDF]
Zhao Wang, Shiqi Wang, Jian Zhang , Shanshe Wang, Siwei Ma
IEEE Data Compression Conference ( DCC2017 ) , pp. 23-32, Snowbird, Utah, USA, Apr. 2017. (Oral) (Top Conference in Data Compression)
• Design and Implementation of Viterbi Encoding and Decoding Algorithm on FPGA.
To use these functions you will need
MATLAB and the
MATLAB Image Processing Toolbox .
You may also want to refer to the MATLAB documentation and the
Image Processing Toolbox documentation
Alternatively you can
use Octave which is
a very good open source alternative to MATLAB. Almost all the functions
on this page run under Octave. See my Notes on using Octave .
An advantage of using Octave is that you can run it on your Android
device. (I can compute phase congruency on my mobile phone!) Get
Corbin Champion's port of Octave at Google play
MATLAB/Octave compatibility of individual function is indicated as follows
- Runs under MATLAB and Octave.
- Only runs under MATLAB.
- Not tested under Octave.
These days I am working almost entirely
in Julia . This is a very exciting
language that is certainly worth a look. At this stage the language
is still young and the image processing and computer vision packages
are very much a work in progress. However, watch this space! Julia
may well become the dominant language for scientific programming.
Collections of functions that I have ported to Julia are indicated
in the code sections below.
I receive so many mail messages regarding this site that I have
difficulty responding to them all. I will endeavor to respond to mail
that directly concerns the use of individual functions. However,
please note I do not have the time to provide an on-line vision
problem solving service!
Please report any bugs and/or suggest enhancements to
Perceptually Uniform Colour Maps
Many widely used colour maps have perceptual flat spots that can
hide features as large as 10% of your total data range. They may also
have points of locally high colour contrast leading to the perception
of false features in your data when there are none. MATLAB's 'hot',
'jet', and 'hsv' colour maps suffer from these problems. Use the
colorcet maps instead! For an
overview of this work and the theory behind it please visit
this page .
- A stand-alone
function that contains pre-generated arrays of my perceptually uniform
Generation and correction of colour maps
If you want to experiment with the generation of your own perceptually
uniform colour maps...
- Colour map generating
function. Select from a large library of colour maps. Colour maps are
defined by B-spline paths through CIELAB space. The parameterisation
along the path is then adjusted to ensure uniform perceptual contrast.
Modify the function to add any new colour maps you want.
Remaps entries in a colour map in order to equalise the perceptual
contrast across the colour map. Used by . Can also be used to
'rescue' some of MATLAB's colour maps.
a linear colour map from [0 0 0] to a specified colour in RGB space.
- Returns three
basis/primary colour maps for generating ternary images. The colour
maps are closely matched in lightness (unlike the RGB primaries).
- Generates a colour map of
random colours. Not perceptually uniform and certainly not useful for
displaying data that varies over a continous range. However, it is
useful for displaying a labeled segmented image.
- Used to
automatically generate the function using
Rendering of images with colour maps
- Applies a
colour map to a single channel image to obtain an RGB result.
- This function is
intended for displaying an image with a diverging colour map. To do
this correctly requires that the desired reference value in the data
is correctly associated with the centre entry of the diverging colour
- This function
displays an image of angular data with a specified colour map. For
angular data to be rendered correctly it is important that the data
values are respected so that data values are correctly assigned to
specific entries in a cyclic colour map. The assignment of values to
colours also depends on whether the data is cyclic over pi, or 2*pi.
This function also allows the colour map encoding of the angular
information to be modulated to represent the
amplitude/reliability/coherence of the angular data.