Image Quality Enhancement using Deep Learning
Anila S
, Abin P Francis , Ajai Saju , Ashwin Sundar
Auto encoder, Enhanced Deep Super Resolution
Image enhancement is a process of improving the visual quality of an image by reducing noise, enhancing details, and correcting distortions. Deep learning techniques have demonstrated promising results in various image processing tasks, including image enhancement. This paper proposes a deep learning-based method for image enhancement, which employs a convolutional neural network (CNN) to learn the relationship between degraded and enhanced images. The proposed method consists of two main components, a degradation network that emulates common image degradations, and an enhancement network that generates the enhanced image from the degraded input image. A large dataset of degraded and corresponding enhanced images is used to train the network. The effectiveness of the proposed method is evaluated on several benchmark datasets, and its performance is compared with existing stateof-the- art methods. Results indicate that the proposed method outperforms existing methods in terms of both objective metrics and subjective visual quality. Furthermore, the proposed method is demonstrated to be effective in various real-world applications, such as low-light image enhancement and image denoising. This study suggests that the proposed method has the potential to enhance the visual quality of images in a variety of applications, including surveillance, medical imaging, and remote sensing.
"Image Quality Enhancement using Deep Learning", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 5, page no.2148 - 2154, May-2023, Available :https://ijsdr.org/papers/IJSDR2305338.pdf
Volume 8
Issue 5,
May-2023
Pages : 2148 - 2154
Paper Reg. ID: IJSDR_206790
Published Paper Id: IJSDR2305338
Downloads: 000347210
Research Area: Computer Science & Technology
Country: Ernakulam, Kerala, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
