Adaptive multi-level wavelet decomposition for efficient image compression
Tugba Ozge Onur
article (Uluslararası, Hakemli) | Yazar(lar): Tugba Ozge Onur | Yıl: 2026 | Dergi/Kurum: PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI | İndeks: WOS.ESCI | DOI: 10.5505/pajes.2025.72279 | Anahtar Kelimeler: Wavelet transform, Image compression, Adaptive quanti
Image compression is a crucial technique for reducing storage requirements and improving transmission efficiency of digital images, especially given the ever-increasing volume of image data. However, conventional lossy compression methods such as JPEG and JPEG2000 often introduce significant quality degradation, particularly when compressing highly detailed images. This study presents an optimized wavelet transform-based image compression method designed to minimize information loss while maximizing compression efficiency. The proposed method integrates adaptive thresholding, the selection of optimized wavelet functions, and multi-level wavelet decomposition to address the limitations of traditional approaches. Specifically, adaptive thresholding is used to dynamically adjust compression parameters, reducing unnecessary data retention, while the wavelet function selection process ensures the most suitable basis for image features. Multi-level wavelet decomposition enables the retention of important image details across various resolution scales, improving compression without compromising visual quality. The performance of the proposed method is evaluated on several image types, including well-known test images, and compared against standard image compression techniques such as JPEG and JPEG2000. Experimental results show that the proposed method outperforms the conventional methods in terms of both compression ratio and image quality preservation, achieving higher Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) scores. The proposed approach is particularly effective for applications requiring high-quality image storage and transmission, such as medical imaging, satellite imagery, and multimedia communication.