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Title: :  FAST IMAGE RESTORATION AND ENHANCEMENT
PaperId: :  23931
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 3 2024
DUI:    16.0415/IJARIIE-23931
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Prof. S. T. BhalshankarMIT College Of Railway Engineering And Research, Barshi, Maharashtra, India,
Tejaswini Ambadas PotabattiMIT College Of Railway Engineering And Research, Barshi, Maharashtra, India,
Pragati Santosh DeshmukhMIT College Of Railway Engineering And Research, Barshi, Maharashtra, India,
Komal Bibhishan DevadeMIT College Of Railway Engineering And Research, Barshi, Maharashtra, India,
Alisha Shabbir PatelMIT College Of Railway Engineering And Research, Barshi, Maharashtra, India,
Vaishali Ramrao WankhedeMIT College Of Railway Engineering And Research, Barshi, Maharashtra, India,

Abstract

Computer Engineering
Image Enhancement, Convolutional Neural Networks, Deep Learning, Transfer Learning.
This paper presents MIRNet-v2, a novel architecture for image restoration that aims to preserve high-resolution spatial details while effectively leveraging contextual information from low-resolution representations. The proposed approach utilizes multi-scale residual blocks with parallel multi-resolution convolution streams, mechanisms for information exchange, non-local attention mechanisms, and attention-based multi-scale feature aggregation. MIRNet-v2 achieves state-of-the-art results across various image processing tasks, including defocus deblurring, image denoising, super-resolution, and image enhancement, as demonstrated through extensive experiments on six real image benchmark datasets. Experiments show that in deep learning, using image enhancement algorithms may improve CNN performance when training complete CNN models, but not all image enhancement algorithms can improve CNN performance; in transfer learning, when fine-tuning the pre- trained CNN model, image enhancement algorithms may reduce the performance of CNN.

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IJARIIE Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, and Vaishali Ramrao Wankhede. "FAST IMAGE RESTORATION AND ENHANCEMENT" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 3 2024 Page 2124-2132
MLA Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, and Vaishali Ramrao Wankhede. "FAST IMAGE RESTORATION AND ENHANCEMENT." International Journal Of Advance Research And Innovative Ideas In Education 10.3(2024) : 2124-2132.
APA Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, & Vaishali Ramrao Wankhede. (2024). FAST IMAGE RESTORATION AND ENHANCEMENT. International Journal Of Advance Research And Innovative Ideas In Education, 10(3), 2124-2132.
Chicago Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, and Vaishali Ramrao Wankhede. "FAST IMAGE RESTORATION AND ENHANCEMENT." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 3 (2024) : 2124-2132.
Oxford Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, and Vaishali Ramrao Wankhede. 'FAST IMAGE RESTORATION AND ENHANCEMENT', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 3, 2024, p. 2124-2132. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/FAST_IMAGE_RESTORATION_AND_ENHANCEMENT_ijariie23931.pdf (Accessed : 20 May 2024).
Harvard Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, and Vaishali Ramrao Wankhede. (2024) 'FAST IMAGE RESTORATION AND ENHANCEMENT', International Journal Of Advance Research And Innovative Ideas In Education, 10(3), pp. 2124-2132IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/FAST_IMAGE_RESTORATION_AND_ENHANCEMENT_ijariie23931.pdf (Accessed : 20 May 2024)
IEEE Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, and Vaishali Ramrao Wankhede, "FAST IMAGE RESTORATION AND ENHANCEMENT," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 3, pp. 2124-2132, May-Jun 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/FAST_IMAGE_RESTORATION_AND_ENHANCEMENT_ijariie23931.pdf [Accessed : 20 May 2024].
Turabian Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, and Vaishali Ramrao Wankhede. "FAST IMAGE RESTORATION AND ENHANCEMENT." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 3 (20 May 2024).
Vancouver Prof. S. T. Bhalshankar, Tejaswini Ambadas Potabatti, Pragati Santosh Deshmukh, Komal Bibhishan Devade, Alisha Shabbir Patel, and Vaishali Ramrao Wankhede. FAST IMAGE RESTORATION AND ENHANCEMENT. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : 20 May 2024]; 10(3) : 2124-2132. Available from: https://ijariie.com/AdminUploadPdf/FAST_IMAGE_RESTORATION_AND_ENHANCEMENT_ijariie23931.pdf
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