Data Structures and Algorithms - Essay Example

while((read = from.Read(buffer, 0, _bufferSize)) > 0) { // Write the buffer (what was actually read) to the output stream huffman.Write(buffer, 0, read); } } } /// Compress a stream of data to an output stream. /// The input stream to be compressed. /// A stream of compressed data. /// /// Compression begins at the current position in the input stream. /// The resulting stream's position is at the end of the current data. /// public static MemoryStream Compress(Stream s) { // Create a new memory stream to hold the compressed data MemoryStream ms = new MemoryStream(); // Compress from s to ms Compress(s, ms); // Return the compressed stream after resetting its position to the beginning return ms; } /// Compress an array of bytes using adaptive Huffman compression.

/// The bytes to be compressed. /// The compressed bytes. public static byte [] Compress(byte [] bytes) { // Create a new memory stream to hold the input uncompressed bytes // and one to hold the output compressed bytes MemoryStream from = new MemoryStream(bytes); MemoryStream to = new MemoryStream(); // Compress from input to output Compress(from, to); // Get the compressed bytes and return them return to.ToArray(); } #endregion #region Decompression /// Decompress a stream of input data to an output stream.

/// The stream containing the data to be decompressed. /// The stream to which the decompressed data should be written. /// /// Reading and writing begins. And therefore, this might be comfortable for usages connected with textual data. Where there is image related data, the exercise might become pretty cumbersome and might not be possible to realize both the spatial and spectral data to be brought under the Huffman Code compression technique. In order to increase the efficiency of coding even while using the text compression techniques.

For this purpose a semi Adaptive Huffman code is practiced to increase the efficiency of the work. Adaptive Huffman coding technique is used to further enhance the efficiency of the compression techniques in realizing smaller file sizes.