FIASCO—An Open-Source Fractal Image and Sequence Codec
The coding method of FIASCO is basically a straightforward generalization of the JPEG method. The JPEG algorithm subdivides an image into a set of image blocks of 8x8 pixels. Each of these blocks is then independently encoded by a linear combination of 64 basis images (the cosine basis, see Resources for details) as shown in Figure 2. The coefficients of these block approximations are then quantized and stored in the output file.
In Figure 2 the image is subdivided into 8x8 pixel blocks. Each of them is approximated by a linear combination of the cosine basis. The approximation coefficients (a and b in the figure) are then quantized and stored in the JPEG file. FIASCO extends this concept in the following ways:
The image is adaptively subdivided into subblocks (squares or rectangles) of different size. Smaller blocks than those used in smooth regions are used in difficult areas.
Each image block is approximated by image blocks of a dynamic dictionary. The dictionary not only contains a fixed set of basis images (e.g., the well-known JPEG cosine images) but also all previously encoded image blocks. This method is related to text compression algorithms, which also use dynamically generated dictionaries (e.g., LZW compression).
When coding videos, only the difference between subsequent frames is encoded by hierarchical motion compensation.
FIASCO exploits self-similarities within single pictures, and also sequences of pictures, to remove spatial, spectral and temporal redundancies, making it a typical fractal coding method.
The FIASCO package is released under the terms of the GNU General Public License and is built up of command line applications and a library to compress, decode and visualize images and videos. You just have to run the typical GNU build process (./configure;make;make install) to compile and install the FIASCO package. FIASCO is entirely written in ANSI C and should compile on most UNIX platforms.
Usage of the commandline FIASCO coder and decoder is similar to the cjpeg and djpeg applications of the IJPEG package (Independent JPEG group), which should be part of every Linux distribution.
cfiasco --quality=10 --output=video.fco frame0*.ppm
The above encodes the given video files (in raw PNM format) with quality ten, writing a single FIASCO file video.fco. Please note that you cannot compare the quality settings of FIASCO with JPEG. The typical quality range of FIASCO is 1-100, which corresponds to a JPEG quality less than five. FIASCO is intended for very low bit rates only; i.e., you cannot compute compressed images that correspond to a JPEG quality of 75.
dfiasco, the FIASCO decoder, is also used like djpeg:
dfiasco --output=image.ppm image.fco
This decodes the given FIASCO file and writes a new image in PNM format. But dfiasco also contains a display module to show video frames in an X11 window. Currently, only an Xlib-based window with the typical set of control buttons is available (play, stop, forward, etc.). Hopefully, this simple decoder and the FIASCO library provides a good starting point for developers to support the FIASCO format in their favorite image and video programs (Mozilla, GIMP, etc.). Please visit the home page of FIASCO to get some compressed images and videos (see Resources).
The coding and decoding functionality of FIASCO is available in a shared library. Data type definitions and function prototypes are provided by the include file fiasco.h, which is installed in the $prefix/include directory.
You can simply compress images or videos in your application by a function call:
fiasco_coder (image_names, fiasco_name, quality, NULL)
This call compresses the image file(s) given by the array image_names with the predefined approximation quality (1.0-100.0) and creates the new FIASCO output file fiasco_name. Several advanced compression parameters can be adjusted by using an optional parameter object which I don't describe here, see the FIASCO manual pages for details.
In order to decode a FIASCO file in your application, you have to instantiate an object of the decoder class fiasco_decoder_t with a call of the constructor function fiasco_decoder_new (fiasco_name, NULL). fiasco_name specifies the file to decode whereas the second parameter is an optional parameter object to adjust the behavior of the decoder.
Individual frames are then decoded by subsequent calls of the method fiasco_decoder_get_frame. These frames are returned in an internal FIASCO format, which then can be rendered in different ways to fit the needs of your application. For more information about the compression library, refer to the manual pages shipped with FIASCO.
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Sponsored by AMD
Built-in forensics, incident response, and security with Red Hat Enterprise Linux 6
Every security policy provides guidance and requirements for ensuring adequate protection of information and data, as well as high-level technical and administrative security requirements for a system in a given environment. Traditionally, providing security for a system focuses on the confidentiality of the information on it. However, protecting the data integrity and system and data availability is just as important. For example, when processing United States intelligence information, there are three attributes that require protection: confidentiality, integrity, and availability.
Learn more about catching the bad guy in this free white paper.
Sponsored by DLT Solutions
| Designing Electronics with Linux | May 22, 2013 |
| Dynamic DNS—an Object Lesson in Problem Solving | May 21, 2013 |
| Using Salt Stack and Vagrant for Drupal Development | May 20, 2013 |
| Making Linux and Android Get Along (It's Not as Hard as It Sounds) | May 16, 2013 |
| Drupal Is a Framework: Why Everyone Needs to Understand This | May 15, 2013 |
| Home, My Backup Data Center | May 13, 2013 |
Enter to Win an Adafruit Pi Cobbler Breakout Kit for Raspberry Pi

It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Pi Cobbler Breakout Kit for Raspberry Pi.
Congratulations to our winners so far:
- 5-8-13, Pi Starter Pack: Jack Davis
- 5-15-13, Pi Model B 512MB RAM: Patrick Dunn
- 5-21-13, Prototyping Pi Plate Kit: Philip Kirby
- Next winner announced on 5-27-13!
Featured Jobs
| Linux Systems Administrator | Houston and Austin, Texas | Host Gator |
| Senior Perl Developer | Austin, Texas | Host Gator |
| Technical Support Rep | Houston and Austin, Texas | Host Gator |
| UX Designer | Austin, Texas | Host Gator |
| Web & UI Developer (JavaScript & j Query) | Austin, Texas | Host Gator |
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?





2 min 24 sec ago
3 min 6 sec ago
2 hours 3 min ago
10 hours 48 min ago
11 hours 22 min ago
12 hours 21 min ago
13 hours 11 min ago
17 hours 13 min ago
21 hours 28 sec ago
21 hours 8 min ago