08-16-2017, 09:02 PM
Abstract
Huffman coding can be used to compress all sorts of data. It is an entropy-based algorithm that relies on an analysis of the frequency of symbols in an array. Huffman coding can be demonstrated most vividly by compressing a raster image. Suppose we have a 5 5 raster image with 8-bit color, i.e. 256 different colors. The uncompressed image will take 5 x 5 x 8 = 200 bits of storage. This compression technique is used broadly to encode music, images, and certain communication protocols. Lossless JPEG compression uses the Huffman algorithm in its pure form. Lossless JPEG is common in medicine as part of the DICOM standard, which is supported by the major medical equipment manufacturers (for use in ultrasound machines, nuclear resonance imaging machines, MRI machines, and electron microscopes). Variations of the Lossless JPEG algorithm are also used in the RAW format, which is popular among photo enthusiasts because it saves data from a camera s image sensor without losing information. This project contains an implementation of HUFFMAN technique for image compression and finally does analysis of technique on basis of PSNR, BER, MSE parameters