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.