Transform Coding Based Image Compression Techniques – A Simulative Investigation

Due to digitized representation of images, an image compression has become the necessity because the digital images are nmhighly data intensive and thus require large storage space and more time to transmit. Image sample values contain some redundant bits along with the information content. By removing these redundant bits image compression can be achieved. This leads an image to be represented using a lower number of bits per pixel, without losing the ability to reconstruct the image. Image coding and compression techniques; convert the images into the form that require low memory storage space, smaller bandwidth for transmission, high PSNR (Peak Signal to Noise ratio) with acceptable image quality. We compared four transform coding based image compression standards i.e. JPEG (Joint Photographic Expert Group), JPEG2000, SPIHT (Set Partitioning in Hierarchical Trees) using 2D-DWT (Discrete Wavelet Transform) and SPIHT using 2D dual-tree DWT using simulation software MATLAB. Our comparison is based on the four performance parameters i.e compression ratio, PSNR, encoding time and decoding time.