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FRESH—FRI-Based Single-Image Super-Resolution Algorithm | Matlab Image Processing IEEE Project

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FRESH—FRI-Based Single-Image Super-Resolution Algorithm | Matlab Image Processing Final Year IEEE project with source code.
To buy this project in ONLINE, Contact:
🚀IEEE Base Paper Title: FRESH—FRI-Based Single-Image Super-Resolution Algorithm.
💡Implementation Code: MATLAB.
🛠️Tool details: MATLABR2013A.
💰Cost (In Indian Rupees): Rs.3000/
📘IEEE Base paper Abstract:
In this paper, we consider the problem of single image super-resolution and propose a novel algorithm that outperforms state-of-the-art methods without the need of learning patches pairs from external data sets. We achieve this by modeling images and, more precisely, lines of images as piecewise smooth functions and propose a resolution enhancement method for this type of functions. The method makes use of the theory of sampling signals with finite rate of innovation (FRI) and combines it with traditional linear reconstruction methods. We combine the two reconstructions by leveraging from the multi-resolution analysis in wavelet theory and show how an FRI reconstruction and a linear reconstruction can be fused using filter banks. We then apply this method along vertical, horizontal, and diagonal directions in an image to obtain a single-image super-resolution algorithm. We also propose a further improvement of the method based on learning from the errors of our super-resolution result at lower resolution levels. Simulation results show that our method outperforms state-of-the-art algorithms under different blurring kernels.
📚REFERENCE:
Xiaoyao Wei, Student Member, IEEE, and Pier Luigi Dragotti, Senior Member, IEEE, “FRESH—FRI-Based Single-Image Super-Resolution Algorithm”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 25, NO. 8, AUGUST 2016.
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Matlab Image Processing Final Year IEEE project with source code.
To buy this project in ONLINE, Contact:
🚀IEEE Base Paper Title: FRESH—FRI-Based Single-Image Super-Resolution Algorithm.
💡Implementation Code: MATLAB.
🛠️Tool details: MATLABR2013A.
💰Cost (In Indian Rupees): Rs.3000/
📘IEEE Base paper Abstract:
In this paper, we consider the problem of single image super-resolution and propose a novel algorithm that outperforms state-of-the-art methods without the need of learning patches pairs from external data sets. We achieve this by modeling images and, more precisely, lines of images as piecewise smooth functions and propose a resolution enhancement method for this type of functions. The method makes use of the theory of sampling signals with finite rate of innovation (FRI) and combines it with traditional linear reconstruction methods. We combine the two reconstructions by leveraging from the multi-resolution analysis in wavelet theory and show how an FRI reconstruction and a linear reconstruction can be fused using filter banks. We then apply this method along vertical, horizontal, and diagonal directions in an image to obtain a single-image super-resolution algorithm. We also propose a further improvement of the method based on learning from the errors of our super-resolution result at lower resolution levels. Simulation results show that our method outperforms state-of-the-art algorithms under different blurring kernels.
📚REFERENCE:
Xiaoyao Wei, Student Member, IEEE, and Pier Luigi Dragotti, Senior Member, IEEE, “FRESH—FRI-Based Single-Image Super-Resolution Algorithm”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 25, NO. 8, AUGUST 2016.
🏷️tags:
#matlabprojects #imageprocessing #ieeeprojects #finalyearprojects #matlabprojectswithsourcecode #computerscienceproject #matlab #miniproject #matlabproject #finalyearprojectideas #academicprojects #majorproject #finalyearproject #ieeeproject #academicproject #miniprojects
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