Tamamlayıcı renk dalgacık dönüşümü kullanılarak renkli görüntülerin gürültüden arındırılması

Öz

RGB renk halkası, tamamlayıcı renklere sahip olduğu için insan görmesinde en anlaşılabilir renk temsili olarak bilinmektedir. Bununla birlikte, renk ilişkileri, dalgacık tabanlı renkli görüntü işleme araçlarında neredeyse hiç rol oynamamaktadır. Bu çalışmada tamamlayıcı renk ilişkileri ve kompleks dalgacık tasarım tekniklerine dayanan, Tamamlayıcı Renk Dalgacık Dönüşümü (TRDD), renkli görüntülerde gürültülerin giderilmesi için kullanılmıştır. Bu dalgacık, RGB renk halkasında bulunan renk eksenleri arasındaki açı ilişkilerinden elde edilen 2π/3 faz farklarına sahip, 2 boyutlu kompleks dalgacıklardan oluşan bir aileden meydana gelmektedir ve yönsel seçicilik bakımdan çok etkilidir. Farklı fazdaki yönlere ait katsayılar kullanılarak çok kanallı renkli görüntülerden gürültü giderme işlemleri gerçekleştirilmiştir. Farklı renkli görüntüler ve gürültü seviyeleri kullanılarak TRDD'nin performansı, tepe sinyal-gürültü oranı, yapısal benzerlik indeksi, ortalama kare hata değerleri ve görsel kaliteye dayalı olarak doğrulanmıştır. TRDD, en gelişmiş çok çözünürlüklü görüntü gürültü giderme algoritmalarıyla karşılaştırılmış ve yöntemin hem niceliksel hem de görsel olarak daha üstün gürültü giderme performansı elde ettiği görülmüştür. Ayrıca TRDD'nin hesaplama süresi analiz edilmiş ve mevcut yaklaşımlarla karşılaştırılmıştır.

Anahtar Kelimeler

• Tamamlayıcı renk dalgacık dönüşümü
• Renkli görüntü gürültü giderme
• Dalgacık eşikleme
• Gauss gürültüsü

Color images denoising using complementary color wavelet transform

Abstract

The RGB color ring is known as the most understandable color representation in human vision, as it has complementary colors. However, color relationships hardly ever play a function in wavelet-primarily based totally color image processing tools. In this study, Complementary Color Wavelet Transform (CCWT), which is supported by complementary color relationships and complex wavelet design techniques, is used to denoise in color images. This wavelet consists of a family of two-dimensional complex wavelets with a phase difference of 2π/3 obtained from the angle relationship between the color axes of the RGB color ring, and is very effective in terms of directional selectivity. By using the coefficients of the directions in different phases, denoising processes are performed from the multi-channel color images. It was validated the performance of CCWT using various color images and noise levels, based on peak signal-to-noise ratio, structural similarity index, mean square error values, and visual quality. CCWT was compared with state-of-the-art multi-resolution image denoising algorithms, and found that the method achieves superior denoising performance both quantitatively and visually. It was also analyzed the computation time of CCWT and compared it with existing approaches.

Keywords

• Complementary color wavelet transform
• Color image denoising
• Wavelet thresholding
• Gaussian noise

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