Volume 22, Issue 2 (12-2025)
ASWTR 2025, 22(2): 48-55 |
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Fateh H, TashnehLab M, Fateh M. Enhancing the Quality of Melanoma Dermatoscopic Images Using Wavelet Coefficients within a Deep Learning Framework. ASWTR 2025; 22 (2) :48-55
URL: http://icml.ir/article-1-675-en.html
URL: http://icml.ir/article-1-675-en.html
Faculty of Electrical and Computer Engineering, K.N.Toosi University of Technology, Tehran, Iran
Abstract: (23 Views)
Background: High-quality medical images improve accuracy in diagnosing diseases. Melanoma is a common and deadly skin cancer. Dermatoscopes offer a non-invasive way to capture skin lesions, but dermatoscopic image quality greatly affects diagnosis.
Methods: We propose a deep learning–based method to enhance dermatoscopic image quality using wavelet detail coefficients. ASuper-Resolution Convolutional Neural Network (SRCNN) estimates high-resolution wavelet coefficients from low-resolution images. This approach enables efficient training with fewer samples and lower computational cost. Refinement of these coefficients leads to better image reconstruction, measured using Peak Signal-to-Noise Ratio (PSNR).
Results: Tests on 180 dermatoscopic images show our method achieves a PSNR of 48.99. Previous approaches reached a maximum PSNR of 44.02.
Conclusion: This result shows our framework can provide high-quality images, supporting more accurate melanoma diagnosis.
Methods: We propose a deep learning–based method to enhance dermatoscopic image quality using wavelet detail coefficients. ASuper-Resolution Convolutional Neural Network (SRCNN) estimates high-resolution wavelet coefficients from low-resolution images. This approach enables efficient training with fewer samples and lower computational cost. Refinement of these coefficients leads to better image reconstruction, measured using Peak Signal-to-Noise Ratio (PSNR).
Results: Tests on 180 dermatoscopic images show our method achieves a PSNR of 48.99. Previous approaches reached a maximum PSNR of 44.02.
Conclusion: This result shows our framework can provide high-quality images, supporting more accurate melanoma diagnosis.
Keywords: Melanoma, Deep Learning, Wavelet Transform, Dermatoscopic Imaging, Image Resolution Enhancement
Educational: Research |
Subject:
General
Received: 2025/09/28 | Accepted: 2025/10/11 | Published: 2025/12/14
Received: 2025/09/28 | Accepted: 2025/10/11 | Published: 2025/12/14
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