Özet:

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.

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