Data compression has important application in the areas of data
transmission and data storage. Many data processing applications
require storage of large volumes of data. A compression is
beneficial from many perspectives. It minimizes the storage
requirement and required bandwidth, as well as transmission time
between the encoder and decoder. Huffman encoding scheme is widely
used in text, image and video compression. Many techniques have
been presented since then. But still this is an important field as
it significantly reduces storage requirement and communication
cost. This research presented a new memory efficient data structure
for the static Huffman tree. Memory efficient representation of
Huffman tree increases the compression ratio of Huffman coding
especially for Repeated and Block Huffman coding. Based on the
memory efficient data structure, a new Huffman decoding algorithm
is presented. The advantage of this decoding process is that it
does not require reconstructing Huffman table or tree in the
receiver end for decoding a compressed file. This type of data
structures will be really applicable for low memory machines.
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