Analyzing Data Compression Techniques for Biomedical Signals and Images Using Downsampling and Upsampling

In recent years, due to the enormous data utility everywhere, the need for data compression grows drastically in almost all fields of science and engineering. A few examples of data compression include such as mobile phones, CD players, DVD players, digital television, etc. Compression can be achieved with lossy or lossless; obviously, the algorithms become tough for the lossless compression for better efficiency. This article focuses mainly on the utility behind the downsampling and upsampling, and hence this would lead to the sub-band coding, which is a widely used data compression technique. During the process of sub-band coding, both the orthogonal and bi-orthogonal filters are used for the averaging and differencing tasks. Simulation results reveal that, as expected, the most energy compaction appears at the low-low sub-images. The Matlab 9.4 tool is used for experimental simulation with the retinal and asthma test images for data compression.