Complexity Reduction in DAT-Based Image Processing

The atomic functions-based image processing system (AFIPS) is based on discrete atomic transform (DAT). It provides a combination of image encryption and compression features with a machine learning-oriented data format. Taking into account the current data processing and analysis trends, applying AFIPS is promising. In this paper, a problem of its complexity reduction is considered. The new coding scheme, which ensures a significant decrease in the number of arithmetic operations, is proposed, and its efficiency exploration is given in terms of different indicators. In particular, it is shown that the proposed modification of AFIPS provides a higher compression ratio and, hence, greater memory savings when applying this algorithm with three modes of the DAT procedure: classic, block-splitting, and chroma-subsampling. Also, the suggested improvement reduces the time complexity that is illustrated by processing a satellite image dataset. In addition, the practical aspects of the further applications, including UAV image processing and analysis, are discussed.