JPEG Image Compression and Decompression using Discrete Cosine Transform (DCT)

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. An Image can be compressed with use of Discrete Cosine Transform (DCT), quantization encoding are the steps in the compression of the Joint Photographic Expert Group (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 (5). These frequency components are then quantized with the standard Q50. Run length coding is used to produce the compressed representation. Distortion between the original image and reconstructed image is measured with Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) with different compression factors. The compression ratio and PSNR values are different for different images. It is found that performance will not remain same for different images even though compression factor was same.