Lossless Grey-scale Image Compression using Source Symbols Reduction and Huffman Coding

Usage of Image has been increasing and used in many applications. Image compression plays vital role in saving storage space and saving time while sending images over network. A new compression technique proposed to achieve more compression ratio by reducing number of source symbols. The source symbols are reduced by applying source symbols reduction and further the Huffman coding is applied to achieve compression. The source symbols reduction technique reduces the number of source symbols by combining together to form a new symbol. Therefore, the number of Huffman code to be generated also reduced. The Huffman code symbols reduction achieves better compression ratio. The experiment has been conducted using the proposed technique and the Huffman coding on standard images. The experiment result has analyzed and the result shows that the newly proposed compression technique achieves 10% more compression ratio than the regular Huffman coding.