CT Image Compression Using Compressive Sensing and Wavelet Transform

Compressive sensing (CS) technique addresses the issue of compressing the sparse signal with a rate below Nyquist rate of sampling. For medical images there are always issues of acquisition time and compression, the compressive sensing is found to be a better technique that works in a manner that it first acquires samples less than signal dimensionality and reconstructs the same signal. In this paper Wavelet transform is applied along with compressive sensing on CT images. Three various measurements (for three compression ratio values) have been taken and calculated PSNR, CoC, and RMSE. As measurements are increased PSNR, CoC and visual quality increases and RMSE decreases. The main observation is that only 60% measurements can reproduce image with PSNR of more than 25 dB and with CoC more than 0.99.