Compression using Matrix Folding Algorithm

Abstract: Space optimization is a particular phenomenon which has puzzled the computer programmers worldwide. More and more data needs to be stored into ever decreasing space. Several techniques are utilized to either decompress the files or better manage the memory. The first aspect involves the mathematics behind the conversion and the second aspect involves physics to store more data on to smaller chips. The proposed formulation i.e. The Matrix Folding Algorithm serves the first aspect of Space optimization by making use of mathematical calculations to reduce the size of a matrix. Matrix Folding Algorithm is a technique to reduce the space occupied by a square matrix to a level of 25% of the original size. The algorithm is based on mathematical calculations applied on the original values in order to double fold the matrix first from right to left and then from bottom to top. Like many other algorithms this one also has limitations that the original matrix should have numbers ranging from 0 through 15 only when we consider a system where the integer takes 2 bytes of space. And the matrix should have numbers ranging from 0 through 255 only when we consider a system where the integer takes 4 bytes of space.

Keywords: Matrix Folding, Dimension reduction, Loss-less compression, Space Complexity, Space Optimization

Recommended Citation: Jindal, G., Sharma, N., Chadha, H., & Pathak, N. (2021). Compression using Matrix Folding Algorithm. 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). https://doi.org/10.1109/icrito51393.2021.9596447

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Collaborators - Dr. Gaurav Jindal, Dr. Neelam Sharma, Dr. Nitish Pathak