Comparative Analysis of Wavelet Families in Image Compression, Featuring the Proposed New Wavelet

Abstract

Image compression is fundamental to the efficient and cost-effective use of digital media, including but not limited to medical imagery, satellite images, and daily photography. Wavelet transform is one of the best methods used in compression. This study conducts a meticulous comparative analysis of various established wavelet families and introduces a novel wavelet named nwi, shedding light on its performance compared to well-established counterparts. This research conducts a meticulous comparative analysis of various wavelet families to assess their performance in image compression. Leveraging quantitative metrics such as Compression Ratio (CR) and Peak Signal-to-Noise Ratio (PSNR), extensive data presented in tables and figures provides a comprehensive overview of the effectiveness of different Wavelet transforms. The results show that an average compression ratio of around 75% can be achieved with a 38 dB PSNR value for all test images. The best result was achieved with the test-2 image from the proposed nwi wavelet. The research evaluates eight wavelet families and shows that the performance of image compression depends on both image type and selected wavelet family while keeping the coding algorithm the same for all calculations of image processing scenarios. This systematic exploration contributes valuable insights to the field, aiding practitioners in selecting optimal Wavelet transforms for diverse image processing applications. In image compression, the introduction of new wavelet families, such as the nwi, has the potential to enhance performance and achieve better results.