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http://dx.doi.org/10.5762/KAIS.2017.18.6.728

A study on image region analysis and image enhancement using detail descriptor  

Lim, Jae Sung (DTaQ(Defence agency for Technology and Quality))
Jeong, Young-Tak (DTaQ(Defence agency for Technology and Quality))
Lee, Ji-Hyeok (DTaQ(Defence agency for Technology and Quality))
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.18, no.6, 2017 , pp. 728-735 More about this Journal
Abstract
With the proliferation of digital devices, the devices have generated considerable additive white Gaussian noise while acquiring digital images. The most well-known denoising methods focused on eliminating the noise, so detailed components that include image information were removed proportionally while eliminating the image noise. The proposed algorithm provides a method that preserves the details and effectively removes the noise. In this proposed method, the goal is to separate meaningful detail information in image noise environment using the edge strength and edge connectivity. Consequently, even as the noise level increases, it shows denoising results better than the other benchmark methods because proposed method extracts the connected detail component information. In addition, the proposed method effectively eliminated the noise for various noise levels; compared to the benchmark algorithms, the proposed algorithm shows a highly structural similarity index(SSIM) value and peak signal-to-noise ratio(PSNR) value, respectively. As shown the result of high SSIMs, it was confirmed that the SSIMs of the denoising results includes a human visual system(HVS).
Keywords
Additive white Gaussian noise(AWGN); noise model; noise randomness; edge strength(ES); edge orientation(EO); binary edge map(Ebinary); detail descriptor; connected component based noise filtering;
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