Hybrid Image Compression Algorithm based on Singular Value Decomposition and Discrete Wavelet Transform

The amount of visual data generated in our daily lives is growing, which makes storage a major challenge. As a result, image compression techniques become important for reducing image size without sacrificing quality. In this paper, we propose an efficient image compression algorithm based on singular value decomposition and discrete wavelet transform to address the challenge of maintaining image quality during compression. The proposed compression algorithm is tested on examples of five images and results are assessed on the two main characteristics peak signal-to-noise ratio (PSNR) and compression ratio and the results are reported in various tables. The tabulated results show that our present approach enhances the peak signal-to-noise ratio (PSNR) that reflects better quality of compressed images. Visual Studio code has been utilized to implement the algorithm. Higher-resolution images provide better results for our algorithm. Bar graphs are also depicted for the comparison of both the proposed algorithms.