Abstract
The work overviews Parallel-Hierarchical Transformation methods, including Wavelet transform and Discrete cosine transform, implementation of Parallel-Hierarchical Transformation on GPU, FPGA and CPU using programming libraries and proprietary hardware solutions. It also discusses the representation of masks, which are crucial in optimizing the transformation process and improving computational efficiency. A comparison with other image processing methods, such as the Fast Fourier Transform and traditional hierarchical techniques. An example of implementation is provided. The study covers advantages and limitations of the parallel-hierarchical transform and its usage in digital image processing. The advantages of PHT, such as improved parallelizability and adaptability to different hardware architectures, e.g. quantum, are examined. The findings offer valuable insights into the potential of PHT for advanced image analysis tasks, facilitating further research and development in the field.