DEĞİŞTİRİLMİŞ AYRIK HAAR DALGACIK DÖNÜŞÜMÜ İLE YENİ BİR HİSTOGRAM EŞİTLEME YÖNTEMİ

Histogram eşitleme dijital görüntülerin kontrastını artırmak için kullanılan yöntemlerden biridir. İdeal histogram eşitleme yöntemlerinde, girdi ve çıktı arasındaki görüntü benzerliğini koruyarak histogramdaki dağılımları tekdüze hale getirerek kontrast gerilmektedir. Frekans alanında yapılan bu çalışmada, Düşük Dinamik Aralığında değiştirilmiş ayrık Haar Dalgacık Dönüşümü ile yeni bir görüntü kontrast germe yöntemi önerilmiştir. Bu yöntemde Olasılık Kütle Fonksiyonunu ile frekansların yüksek geçiş kanalında gürültülü frekanslara bir baskılama işlemi gerçekleştirilmiştir. Daha sonra yapılan frekans dönüşümlerinde histogram frekansların dinamik aralıklarında önemli bir azalma sağlanmıştır. Frekans alanındaki bu işlem görüntüde standart sapmanın artmasını sağlayarak görüntü kalitesinin iyileşmesini sağlar. Kıyaslamalı bir veri seti üzerinde yapılan deneysel çalışmalarda, önerilen yöntem konvansiyonel metotlarla kıyaslanmış ve umut verici sonuçlar elde edilmiştir. Görüntü kalitesi değerlendirme metriklerinden Tepe Sinyal Gürültü Oranı (PSNR), Ortalama Kare Hata (MSE), Yapısal Benzerlik Endeks Ölçütü (SSIM) ve Kontrast değeri deneysel çalışmalarda kullanılmıştır. Önerilen bu yaklaşım ile elde edilen sonuçlar diğer algoritmaların sonuçları ile kıyaslandığında hem kalitatif hem de kantitatif açıdan başarılı bulunmuştur.

Anahtar Kelimeler:

Düşük Dinamik Aralığı, Haar Dalgacık Dönüşümü, Histogram Eşitleme, Kontrastı İyileştirme

A NEW HISTOGRAM EQUALIZATION METHOD WITH MODIFIED DISCRETE HAAR WAVELET TRANSFORM

Histogram equalization is one of the methods used to increase the contrast of digital images. In the ideal histogram equalization methods, the contrast are stretched by preserving the image similarity between input and output images, making the distributions in the histogram uniform. In this study conducted in the frequency domain, a new image contrast stretching method with Haar Wavelet Transform (HWT) in Low Dynamic Range is proposed. In this method, using the Probability Mass Function (PMF), a suppression process is applied to the noisy frequencies in the high pass channel of the frequencies. Subsequent frequency transformations provide a feasible reduction in the dynamic range of histogram frequencies. This process in the frequency domain improves the image quality by increasing the standard deviation in the image. In experimental studies over a benchmarking dataset, the proposed method is compared with conventional methods and promising results are obtained. In the experimental studies, Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index Measurement (SSIM) and Contrast value, which are among the image quality evaluation metrics, are used. In this proposed approach, image quality is evaluated both qualitatively and quantitatively assessments, and successful results are obtained.

Keywords:

Low Dynamic Range, Haar Wavelet Transform, Histogram Equalization, Contrast Enhancement,

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