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Journals / Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi / 2026 / Cilt: 32 Sayı: 3

Adaptive multi-level wavelet decomposition for efficient image compression

Etkin görüntü sıkıştırma için adaptif çok seviyeli dalgacık dönüşümü yöntemi

Tuğba Özge Onur

Pages
477–485
Publication Date
2026-06-05
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Abstract

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.

Özet

Görüntü sıkıştırma, özellikle görüntü verilerinin giderek artan hacmi göz önüne alındığında dijital görüntülerin depolama gereksinimlerini azaltmak ve iletim verimliliğini artırmak amacıyla kullanılan kritik bir tekniktir. Ancak, JPEG ve JPEG2000 gibi geleneksel kayıplı sıkıştırma yöntemleri, özellikle yüksek detaylı görüntüleri sıkıştırırken önemli kalite bozulmalarına yol açar. Bu çalışma, bilgi kaybını minimize ederken sıkıştırma verimliliğini maksimize etmek amacıyla optimize edilmiş bir dalgacık dönüşümü tabanlı görüntü sıkıştırma yöntemi sunmaktadır. Önerilen yöntem, geleneksel yaklaşımların sınırlamalarını aşmak için adaptif eşikleme, optimize edilmiş dalgacık fonksiyonları seçimi ve çok seviyeli dalgacık dekompozisyonunu entegre etmektedir. Özellikle, adaptif eşikleme, sıkıştırma parametrelerini dinamik olarak ayarlamak için kullanılarak, gereksiz veri saklamayı azaltırken, dalgacık fonksiyonu seçimi, görüntü özellikleri için en uygun temeli sağlamaktadır. Çok seviyeli dalgacık dekompozisyonu, çeşitli çözünürlük ölçeklerinde önemli görüntü detaylarının korunmasını sağlayarak görsel kaliteyi bozmadan sıkıştırmayı iyileştirir. Önerilen yöntemin performansı, iyi bilinen test görüntüleri üzerinde değerlendirilmiş ve JPEG ve JPEG2000 gibi standart görüntü sıkıştırma teknikleriyle karşılaştırılmıştır. Deneysel sonuçlar, önerilen yönteminin hem sıkıştırma oranı hem de görüntü kalitesinin korunması açısından geleneksel yöntemleri geride bıraktığını, daha yüksek Tepe Sinyal-Gürültü Oranı (PSNR) ve Yapısal Benzerlik Endeksi (SSIM) puanları elde ettiğini göstermektedir. Önerilen yaklaşım, yüksek kaliteli görüntü depolama ve iletimi gerektiren uygulamalarda, örneğin tıbbi görüntüleme, uydu görüntülemesi ve multimedya iletişimi gibi alanlarda etkilidir.

Keywords
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Cite This Article

Onur, T. Ö. (2026). Adaptive multi-level wavelet decomposition for efficient image compression. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, Cilt: 32 Sayı: 3, 477–485. https://doi.org/10.5505/pajes.2025.72279

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