Future studies could investigate the use of .rar compression for specific image types (e.g., medical images, natural images) and explore the development of new compression algorithms optimized for image data.
Our results show that .rar compression can achieve significant reductions in file size, with an average compression ratio of 2.5:1. However, the compression ratio varied widely depending on the image type and compression settings. We also found that .rar compression can result in some loss of image quality, particularly for images with high-frequency content. The PSNR and SSIM values for the compressed images ranged from 20 to 40 dB and 0.5 to 0.9, respectively. Computational complexity was found to be relatively high, with an average compression time of 10 seconds and decompression time of 5 seconds per image. of Images.rar
In conclusion, this study provides an exploratory analysis of .rar compression for images. While .rar can achieve significant reductions in file size, the trade-offs in terms of image quality and computational complexity must be carefully evaluated. The results of this study can inform the use of .rar compression for images in various applications. Future studies could investigate the use of