Date of Publication :30th March 2018

Abstract: Digital image compression is a method of image data reduction to save storage space. Image compression is the process of reducing the size of the image that will enhance images sharing, image transmission and easy storage of the image. There are two types of image compression techniques. In Lossy compression, the compressed image is not equal to the original image; it means the quality of compressed image is less than the original image. In Lossless compression the compressed image is exactly equal to the original image. In this work, the analysis of different format of images have been implemented using the Lossless image compression techniques such as Huffman coding, EZW and SPIHT. Huffman encoding technique basically works on the rule of probability distribution. The principle is to reduce the size of the image by removing redundancies. Less number of bits is used to encode the image. Huffman encoding method is used in JPEG image. Set partitioning in hierarchical trees (SPIHT) is a waveletbased image compression technique. It gives good image compression ratios and image quality. EZW method is based on progressive encoding to compress an image. Experimental result was carried out on four types of image format such as .bmp, .jpg, .png, .tif. The Performance metrics such as Peak signal-to-noise ratio (PSNR), Compression Ratio (CR), Mean square error (MSE), Bits per pixel (BPP) were measured for each format of images

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