Görüntü Sıkıştırmada Dalgacık Ailelerinin Karşılaştırmalı Analizi ve Yeni bir Dalgacık Ailesi Önerisi

Year 2024, Volume: 19 Issue: 1, 279 - 294, 28.03.2024

İbrahim Öz

https://doi.org/10.55525/tjst.1428424

Abstract

Görüntü sıkıştırma, tıbbi görüntülerden uydu görüntülerine ve günlük fotoğrafçılığa kadar dijital medyanın verimli ve maliyet etkili kullanımı için temel bir gerekliliktir. Dalgacık dönüşümü, görüntü sıkıştırmada kullanılan en iyi yöntemlerden biridir. Bu araştırma, en çok bilinen dalgacık ailelerinin görüntü sıkıştırma performansını çeşitli analizlerle değerlendirmiştir. İlave olarak nwi adlı yeni bir dalgacık ailesi üretilmiş ve performansı bilinen dalgacık aileleri ile karşılaştırılmıştır. Sıkıştırma Oranı (CR) ve Tepe Sinyal-Gürültü Oranı (PSNR) gibi nicel ölçüleri kullanarak, tablolar ve şekillerde sunulan sonuçlar, farklı dalgacık dönüşümlerinin performansını göstermektedir. Sonuçlar, tüm test görüntüleri için ortalama %75 sıkıştırma oranının 38 dB PSNR değeri ile elde edilebileceğini göstermektedir. En iyi sonuç, önerilen NWI dalgacığı ile test-2 görüntüsünde sıkıştırma performansı (CP) 3312,08 değeri ile elde edilmiştir. Bu çalışmada, sekiz dalgacık ailesi değerlendirilmekte ve görüntü sıkıştırma performansının hem görüntü türüne hem de seçilen dalgacık ailesine bağlı olduğu sonucu çıkmaktadır. Kodlama algoritması tüm dalgacık aileleri için aynı tutularak sadece dalgacık dönüşüm performansı analiz edilmiştir. Görüntü sıkıştırmada yeni ve etkili dalgacık ailelerinin gerçekleştirilebileceği NWI önerisinde olduğu gibi gösterilmiştir.

Keywords

Dalgacık, görüntü sıkıştırma, sıkıştırma oranı, sinyal gürültü oranı

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 new wavelet for image compression (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. 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, with a compression performance (CP) of 3312.08, using 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. In image compression, introducing new wavelet families, such as the NWI, can enhance performance and achieve better results.

Keywords

Wavelet, image compression, image processing, compression ratio, signal-to-noise ratio

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