I have to decide the area of research for my Master's and would like to know the current research trend in the field of DSP/ image processing.
I really did some research on this field. I focused on the image processing for vision-based navigation. As far as I know, there have been a lot of algorithms of image processing, one of the trend I believe is how to simplify the complexity. I think it's also the target for DSP processing. I tried to use the Neural Networks to detect the edge of craters from optical image, and the computational burden is really heavy. Maybe parallel computing is a good choice. Tank you!
I agree that compressed sensing is a very interesting area of active research. As a mathematical technique that permits violation of the Nyquist criteria under certain circumstances, its implications are broad and not yet fully understood. Similar to the transition from TDMA to CDMA, compressed sensing exploits abstractions that open up a new, multi-dimentional space to explore with axes like: quality, iterations, and %-sampled, which can be customized to the application and combined with existing techniques like parallel imaging in MRI.
http://nuit-blanche.blogspot.com/p/teaching-compressed-sensing.html
Today researchers showing them self more modern, giving the reference, of readily available web software, instead understanding, to prove, their exposer of subject, in research of digital signal processing, important is individual thinking. understanding and approach to solve problem. For digital signal processing,there are many algorithms ( Forrier, Walse, Hartley and the modification of it etc. etc.), all are having its own importance to give accurate result (for different frequencies, and type of signal(bio medical ,sasemic, sound etc.). Instead of using readily available software, try to understand them., to find which algorithm is more suitable for your signal frequency and type,, why? justify giving comparative result, if possible develop a new software, publish paper on your work, to world.
Brain-computer interface could also be an interesting field to go.
Image fusion - combining the outputs from several imaging sensors, which do not share the same optics and may or may not be co-registered or even the same scale. For instance a visible and infra-red sensor looking at the same scene.
Medical Imaging is hot research area like Brain Tumor, Lung Cancer, Breast Cancer, Liver Cancer, Knee Joint Problem etc
Image denoisy, Watermarking and its applications to communication problems and medical image processing are interesting fields of research.
Image reconstruction (with applications in Wireless Communications, Satellite and Space Communication, Image and video Communications, etc), and Medical imaging with algorithms for early diagnosis are very very hot research areas
Image Stitching, Image Fusion, Autonomous Image Processing for noise reduction, object detection and recognition are some of recent trends
well,,,medical image processing has grown into a potential area with big data analytics...
Digital Image Forensics may be another area of research where there are alot of open problems that need to addressed.
Sparse coding, compressed sensing, Artificial Intelligence and Machine Learning.
Please go through the web site of University of Waterloo. There are some hot areas of image processing:
https://uwaterloo.ca/vision-image-processing-lab/research-topics
Image forensics is one of the hot research area with application to deep learning
Yes, Medical Image processing is an active research right now. Early detection for cancer diseases is good.
brain image processing is very wonderfull but MIMO is interesing too.
The brain is the best way to handle images, but with the development of means and technology, image processing has become easier and better through radiation, television imaging,
Human-Machine interface through EEG signals, Image understanding, pattern recognition etc.
Digital Signal and Image Processing; Image, Video and Audio Coding; Medical Image processing & Deep Learning; Information Theory; Machine Learning.
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