A new approach for image compression using normal matrices
This work addresses image compression for applications needing efficient processing, but it appears incremental as it builds on known matrix techniques without clear broad impact.
The paper tackles image compression by using eigenvalue decomposition of normal matrices to transform images, resulting in methods that require fewer and easier computations compared to existing approaches.
In this paper, we present methods for image compression on the basis of eigenvalue decomposition of normal matrices. The proposed methods are convenient and self-explanatory, requiring fewer and easier computations as compared to some existing methods. Through the proposed techniques, the image is transformed to the space of normal matrices. Then, the properties of spectral decomposition are dealt with to obtain compressed images. Experimental results are provided to illustrate the validity of the methods.