A study on discrete wavelet transform compression algorithm for medical images

Image compression is play vital role in medical area. In health field the bulk of medical image data produced every day is ever growing, mainly in grouping with the improved scanning resolutions and the importance of volumetric medical image data sets. In this work, six image compression methods are simulated. They are Karhunen-Loeve Transform (KLT), Walsh-Hadamard Transform (WHT), Fast Fourier Transform (FFT), Sparse Fast Fourier Transform (SFFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). The results of simulation are shown and compared different quality parameters of it are by applying on various lung cancer Computed Tomography (CT) scan medical images. The Discrete Wavelet Transform (DWT) method algorithm was given better results like Compression Ratio (CR), Structural Content (SC), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) compare to other transform methods. The Discrete Wavelet Transform (DWT) technique given improved result compared with other methods in all evaluation measures