Dynamic Digital Radiography: A Moving Perspective on Medical Imaging
In the ever-evolving landscape of medical imaging technology, advancements continue to push the boundaries of what’s possible. One such innovation that’s revolutionizing the field is Dynamic Digital Radiography (DDR). This groundbreaking technique offers unprecedented insights into the human body’s dynamics, providing healthcare professionals with a dynamic view of anatomical structures in…
Literature Review on Single Image Super Resolution
by Shalini Dubey | Prof. Pankaj Sahu | Prof. Surya Bazal" Literature Review on Single Image Super Resolution"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd18339.pdf
Direct URL: http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/18339/literature-review-on-single-image-super-resolution/shalini-dubey
paper publication for engineering, engineering journal, ugc approved journals for engineering
In this paper, a detailed survey study on single image super-resolution (SR) has been presented, which aims at recovering a high-resolution (HR) image from a given low-resolution (LR) one. It is always the research emphasis because of the requirement of higher definition video displaying, such as the new generation of Ultra High Definition (UHD) TVs. Super-resolution (SR) is a popular topic of image processing that focuses on the enhancement of image resolution. In general, SR takes one or several low-resolution (LR) images as input and maps them as output images with high resolution (HR), which has been widely applied in remote sensing, medical imaging, biometric identification.
Single Image Super Resolution using Interpolation and Discrete Wavelet Transform
by Shalini Dubey | Prof. Pankaj Sahu | Prof. Surya Bazal ""Single Image Super Resolution using Interpolation & Discrete Wavelet Transform""
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd18340.pdf
Direct Link: http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/18340/single-image-super-resolution-using-interpolation-and-discrete-wavelet-transform/shalini-dubey
call for paper life sciences, life sciences journal, research papers
An interpolation-based method, such as bilinear, bicubic, or nearest neighbor interpolation, is regarded as a simple way to increase the spatial resolution for the LR image. It uses the interpolation kernel to predict the missing pixel values, which fails to approximate the underlying image structure and leads to some blurred edges. In this work a super resolution technique based on Sparse characteristics of wavelet transform. Hence, we proposed a wavelet based super-resolution technique, which will be of the category of interpolative methods, using sparse property of wavelets. It is based on sparse representation property of the wavelets. Simulation results prove that the proposed wavelet based interpolation method outperforms all other existing methods for single image super resolution. The proposed method has 7.7 dB improvement in PSNR compared with Adaptive sparse representation and self-learning ASR-SL 1 for test image Leaves, 12.92 dB improvement for test image Mountain Lion and 7.15 dB improvement for test image Hat compared with ASR-SL 1 . Similarly, 12 improvement in SSIM for test image Leaves compared with 1 , 29 improvement in SSIM for test image Mountain Lion compared with 1 and 17 improvement in SSIM for test image Hat compared with 1 .
Ein bereits etwas älteres aber immer noch unglaubliches Experiment. Durch das Messen von Gehirnaktivitäten in bestimmten Regionen, ist es möglich, den Gedanken des Probanden zu rekonstruieren. Dabei wird wie folgt vorgegangen:
Die Testperson schaut sich Filmausschnitte an, dabei wird die Gehirnaktivität gemessen.
Man trainiert ein computergestütztes Übersetzungsmodell, dass zwischen Gehirnaktivität und Ecken, Kanten und Formen übersetzen kann
Nun zeigt man der Testperson neue Filmausschnitte und misst dabei die resultierende Gehirnaktivität. Das Computermodell sucht sich aus Youtube dabei 100 Clips aus, für die man eine sehr ähnliche Gehirnaktivität vorhersagt und berechnet das Mittel der Bilder um die erwünschte Rekonstruktion zu erhalten.
Mehr dazu: http://gallantlab.org/publications/nishimoto-et-al-2011.html