source: www/study/index.html @ 2223

Revision 2223, 5.2 KB checked in by sam, 5 years ago (diff)
  • Small reorganisation of chapter 4.
  • Show the results of the HVS on an 8×8 Bayer dither.
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7<head>
8   <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
9   <meta name="GENERATOR" content="vim" />
10   <meta name="Author" content="sam@zoy.org (Sam Hocevar)" />
11   <meta name="Description" content="Libcaca study: the science behind colour ASCII art" />
12   <meta name="Keywords" content="libcaca, ASCII, ASCII ART, console, text mode, ncurses, slang, AAlib, dithering, thresholding" />
13   <title>Libcaca study: the science behind colour ASCII art</title>
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19<body>
20
21<?php include($_SERVER["DOCUMENT_ROOT"]."/header.inc"); ?>
22
23<p> <span style="color: #aa0000; font-weight: bold;">Warning</span>: this
24document is still work in progress. Feel free to send comments but do not
25consider it final material. </p>
26
27<!--<div style="float: left;">
28   <a href=""></a>
29</div>-->
30<div style="float: right;">
31   <a href="part1.html">&gt;&gt;&gt; Colour quantisation</a>
32</div>
33
34<br style="clear: both;" />
35
36<h2> Libcaca study: the science behind colour ASCII art </h2>
37
38<p> This document is an attempt at extending the leverage of skilled
39resources by uncovering and addressing the challenges the industry faces
40today in the area of colour ASCII art generation. </p>
41
42<p> Seriously, guys. If you think that what libcaca does is easy, you either
43don’t know what you are talking about, or we want you in the team. </p>
44
45<h3> Foreword </h3>
46
47<p> Meet Lena. She will guide us through this document, because the
48seriousness of a scientific document in the area of computer graphics can
49be measured by the number of times Lena appears in it. She truly is the
50<i>Mona Lisa</i> of image processing. [2] </p>
51
52<p style="text-align: center;">
53  <img src="lena256.png" width="256" height="256"
54       class="inline" alt="Lena (256×256)" />
55  <img src="gradient256.png" width="64" height="256"
56       class="inline" alt="colour gradient (64×256)" />
57  <img src="lena256bw.png" width="256" height="256"
58       class="inline" alt="Lena (256×256BW)" />
59  <img src="gradient256bw.png" width="32" height="256"
60       class="inline" alt="greyscale gradient (32×256)" />
61</p>
62
63<p> This document makes a lot of assumptions, such as the fact that input
64images are made of pixels that have either one (grey level) or three (red,
65green and blue) values uniformly spread between 0 and 1 (with regards to
66human contrast perception). Real life is more complicated than that, but
67that is beyond the scope of this document for now. </p>
68
69<h3> Table of contents </h3>
70
71<ul>
72  <li> <a href="part1.html">1. Colour quantisation</a>
73    <ul>
74      <li> 1.1. Black and white thresholding </li>
75      <li> 1.2. Greyscale thresholding </li>
76      <li> 1.3. Dynamic thresholding </li>
77      <li> 1.4. Random dithering </li>
78    </ul>
79  </li>
80  <li> <a href="part2.html">2. Halftoning</a>
81    <ul>
82      <li> 2.1. Halftoning patterns </li>
83      <li> 2.2. Screen artifacts </li>
84      <li> 2.3. Ordered dithering </li>
85      <li> 2.4. Random ordered dithering </li>
86      <li> 2.5. Non-rectangular dither tiles </li>
87      <li> 2.6. Supercell dithering </li>
88      <li> 2.7. Void and cluster method </li>
89    </ul>
90  </li>
91  <li> <a href="part3.html">3. Error diffusion</a>
92    <ul>
93      <li> 3.1. Floyd-Steinberg and JaJuNi error diffusion </li>
94      <li> 3.2. Floyd-Steinberg derivatives </li>
95      <li> 3.3. Changing image parsing direction </li>
96      <li> 3.4. Variable coefficients error diffusion </li>
97      <li> 3.5. Block error diffusion </li>
98      <li> 3.6. Sub-block error diffusion </li>
99      <li> 3.7. Direct binary search </li>
100    </ul>
101  </li>
102  <li> <a href="part4.html">4. Model-based dithering</a>
103    <ul>
104      <li> 4.1. Gaussian human visual system model </li>
105      <li> 4.2. Direct binary search </li>
106      <li> 4.3 Comparing dithering algorithms </li>
107    </ul>
108  </li>
109  <li> <a href="part5.html">5. Greyscale dithering</a>
110    <ul>
111      <li> 5.1. Introducing gamma </li>
112      <li> 5.2. Gamma correction </li>
113      <li> 5.3. Greyscale sub-block error diffusion </li>
114    </ul>
115  </li>
116  <li> <a href="part6.html">6. Colour dithering</a>
117    <ul>
118      <li> 6.1. Separate-space dithering </li>
119      <li> 6.2. Accounting for other dimensions </li>
120      <li> 6.3. Reducing visual artifacts </li>
121      <li> 6.4. Colour sub-block error diffusion </li>
122    </ul>
123  </li>
124  <li> <a href="part7.html">7. Photographic mosaics</a>
125    <ul>
126      <li> 7.1. Image classification </li>
127      <li> 7.2. Error diffusion </li>
128      <li> 7.3. Colour ASCII art </li>
129    </ul>
130  </li>
131  <li> <a href="biblio.html">Bibliography</a> </li>
132  <li> <a href="source.html">Source code</a> </li>
133</ul>
134
135<!--<div style="float: left;">
136   <a href=""></a>
137</div>-->
138<div style="float: right;">
139   <a href="part1.html">&gt;&gt;&gt; 1. Colour quantisation</a>
140</div>
141
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144
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