Huffman codes
In telecommunication, how do we represent a
set of messages, each with an access
frequency, by a sequence of 0’s and 1’s?
To minimize the transmission and decoding
costs, we may use short strings to represent
more frequently used messages.
This problem can by solved by using an
extended binary tree which is used in the 2-
way merging problem.
All of Java s Input/Output (I/O) facilities are based on streams, which provide simple ways to read and write data of different types. Java provides many different kinds of streams, each with its own application. The universe of streams is divided into four large categories: input streams and output streams, for reading and writing binary data and readers and writers, for reading and writing textual (character) data. You re almost certainly familiar with the basic kinds of streams--but did you know that there s a CipherInputStream for reading encrypted data? And a ZipOutputStream for automatically compressing data? Do you know how to use buffered streams effectively to make your I/O operations more efficient? Java I/O, 2nd Edition has been updated for Java 5.0 APIs and tells you all you ever need to know about streams--and probably more.
HDFDUMP and BRFDUMP are utility programs developed for use with MISR data
files. HDFDUMP will extract data from a MISR file in the HDF-EOS grid format
(MISR Level 1B2 and Level 2 files) and writes unformatted binary files. BRFDUMP
calculates radiances and bidirectional reflectance factors (BRF) from MISR Level 1B2
files and creates unformatted binary files.
Very good Java Applet used to animate Inserting, Deleting and Searching (Preorder & Postorder algorithm) nodes in binary Trees. This is a part of mine students project.
You can use and redistribute the source code absolutelly free!
OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images.
A few drivers for the Motorola C380 s celluar phone hardware with a simple test application. It s configured to build a binary that is to be uploaded at 0x03fd0000 and run at 0x03fd0010
Huffman codes
1.In telecommunication, how do we represent a set of messages, each with an access frequency, by a sequence of 0 s and 1 s?
2.To minimize the transmission and decoding costs, we may use short strings to represent more frequently used messages.
3.This problem can be solved by using an extended binary tree which is used in the 2-way merging problem.
the sourse code is
to encode and decode the Huffman.
) Compression using huffman code
-with a number of bits k per code word
-provide huffman table
Huffman coding is optimal for a symbol-by-symbol coding with a known input probability distribution.This technique uses a variable-length code table for encoding a source symbol. The table is derived in a particular way based on the estimated probability of occurrence for each possible value of the source symbol .Huffman coding uses a specific method for representing each symbol, resulting in a prefix code that expresses the most common characters using shorter strings of bits than those used for less common source symbols.The Huffman coding is a procedure to generate a binary code tree.
