The need for an efficient technique for compression of Images is ever increasing because the raw images need large amounts of disk space seems to be a big disadvantage during transmission and storage. Image compression is the application of data compression on digital images. Digital images contain large amount of digital information that need effective techniques for storing and transmitting large volume of data. Image compression techniques are used for reducing the amount of data required to represent a digital image This paper aims at the analysis of compression using DCT and Huffman transform by selecting proper better result for PSNR, compression ratio, RMSE have been obtained.In this paper we proposed the lossless method of image compression and decompression using a simple coding technique called Huffman coding. This technique is simple in implementation and utilizes less memory. A software algorithm has been developed and implemented to compress and decompress the given image using Huffman coding techniques in a MATLAB platform. An Image can be compressed with use of Discrete Cosine Transformation (DCT), quantization encoding are the steps in the compression of the JPEG image format. The 2-D Discrete Cosine transform is used to convert the 8×8 blocks of image into elementary frequency components .The frequency components(DC and AC) are reduced to zero during the process of quantization which is a lossy process .The quantized frequency components are coded into variable length code words using encoding process. Distortion between the original image and reconstructed image is measured with PSNR (peak signal to noise ratio) with different compression factors. The compression ratio and PSNR values are different for different images.
