This PNG Delphi version 1.56 documentation (this version is a major rewrite intended to replace the previous version, 1.2).
Improvements in this new version includes:
This new version allows the programmer to not use Delphi heavy units which will greatly reduce the size of the final executable.
Read more about this feature here.
Most, if not all, Portable Network Graphics features as CRC checking are now fully performed.
Error on broken IMAGEs are now better handled using new exception classes.
The IMAGEs may be saved using interlaced mode also.
Transparency information won t be discarted after the image is loaded any more.
Most of the IMAGEs are decoded much faster now.
The IMAGEs will be better encoded using fresh new algorithms.
IMPORTANT! Now transparency information is used to display IMAGEs.
DIGITAL IMAGERY is pervasive in our world today. Consequently,
standards for the efficient representation and
interchange of digital IMAGEs are essential. To date, some of
the most successful still image compression standards have resulted
from the ongoing work of the Joint Photographic Experts
Group (JPEG). This group operates under the auspices of Joint
Technical Committee 1, Subcommittee 29, Working Group 1
(JTC 1/SC 29/WG 1), a collaborative effort between the International
Organization for Standardization (ISO) and International
Telecommunication Union Standardization Sector (ITUT).
Both the JPEG [1–3] and JPEG-LS [4–6] standards were
born from the work of the JPEG committee. For the last few
years, the JPEG committee has been working towards the establishment
of a new standard known as JPEG 2000 (i.e., ISO/IEC
15444). The fruits of these labors are now coming to bear, as
JPEG-2000 Part 1 (i.e., ISO/IEC 15444-1 [7]) has recently been
approved as a new international standard.
Wavelets have widely been used in many signal and image processing applications. In this paper, a new
serial-parallel architecture for wavelet-based image compression is introduced. It is based on a 4-tap wavelet
transform, which is realised using some FIFO memory modules implementing a pixel-level pipeline
architecture to compress and decompress IMAGEs. The real filter calculation over 4 · 4 window blocks is
done using a tree of carry save adders to ensure the high speed processing required for many applications.
The details of implementing both compressor and decompressor sub-systems are given. The primarily analysis
reveals that the proposed architecture, implemented using current VLSI technologies, can process a
video stream in real time.
KVM (for Kernel-based Virtual Machine) is a full virtualization solution for Linux on x86 hardware. It consists of a loadable kernel module (kvm.ko) and a userspace component.
Using KVM, one can run multiple virtual machines running unmodified Linux or Windows IMAGEs. Each virtual machine has private virtualized hardware: a network card, disk, graphics adapter, etc.
The kernel component of KVM is included in mainline Linux, and will appear in Linux 2.6.20.
KVM is open source software.
video editing for is streamlined for fast linear operations over video. It has batch-processing capabilities for processing large numbers of files and can be extended with third-party video filters. VirtualDub is mainly geared toward processing AVI files, although it can read (not write) MPEG-1 and also handle sets of BMP IMAGEs.
A general technique for the recovery of signi cant
image features is presented. The technique is based on
the mean shift algorithm, a simple nonparametric pro-
cedure for estimating density gradients. Drawbacks of
the current methods (including robust clustering) are
avoided. Feature space of any nature can be processed,
and as an example, color image segmentation is dis-
cussed. The segmentation is completely autonomous,
only its class is chosen by the user. Thus, the same
program can produce a high quality edge image, or pro-
vide, by extracting all the signi cant colors, a prepro-
cessor for content-based query systems. A 512 512
color image is analyzed in less than 10 seconds on a
standard workstation. Gray level IMAGEs are handled
as color IMAGEs having only the lightness coordinate
