Comparative Study of Discrete Wavelet Transforms in image Processing using LabVIEW 2023

Image processing has an important rule of ​​the modern emerging research areas that is based on discrete wavelets transforms due to their abilities to represent images at multiple resolutions efficiently. Particularly, this multiple resolution analysis is so useful in many applications such as image compression, denoising, texture analysis, and feature extraction. In this work, A newfound proposed LabVIEW2023 simulation was designed to produce a comparative study between several test images using different types of the most common discrete wavelets transforms (DWT). The comparison was based on calculation of the total evaluation time needed for the image decomposition process and also made a study for image edge detection in terms of different threshold ratios and different image pyramid levels. The discrete wavelets transform (DWT) that used to achieve these comparisons analysis are the orthogonal and biorthogonal wavelets families. The new LabView 2023 simulation design Enviroments exemplified that it is an acqurate, simple, typical and speedy tool to give the best of the desired results. The final results showed the effectiveness of biorthogonal wavelet transform (bior6-8) over the other discrete wavelets transforms in terms of image decomposition and also for image edge detection in the different image pyramid levels.