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Major Research Areas/Interests/Projects



I. Analysis & PDEs with Image Processing Applications
Nonlinear, anisotropic diffusion PDEs, Weak/viscosity/dissipative/Young measure solutions, Perona-Malik type diffusion PDEs, variable exponent PDEs, p-Laplacian, p(t,x)-Laplacian, complex diffusion, higher order PDEs, adaptive PDEs and computational methods (Finite Differences, Finite Elements) for solving them are major themes. Linear, nonlinear scale space theory and applications - smoothing, denoising, segmentation, decomposition.

Project pages:
1. Mono-channel: CoupledPDEs, AFBD, ABO4, Fractional, Infinity, Rinse, Ahana (coming soon)
2. Multi-channel : MultiAD, VTV-denoise, CMAC, VarEx, MMIS, CEDzoo, Hyper (coming soon)

Selected publications:
  • V. B. S. Prasath, A. Singh. "Multispectral image denoising by well-posed anisotropic diffusion with channel coupling. International Journal of Remote Sensing, 31(08):2091-2099, 2010. [MultiAD]

  • V. B. S. Prasath, A. Singh. "Well-posed inhomogeneous nonlinear diffusion scheme for digital image denoising". Journal of Applied Mathematics, Vol. 2010, Article ID 763847, 15 pp, 2010

  • V. B. S. Prasath, A. Singh. "An adaptive anisotropic diffusion scheme for image restoration and selective smoothing", International Journal of Image and Graphics, 12(1):18pp, 2012.
  • V. B. S. Prasath, D. Vorotnikov. "On a system of adaptive coupled PDEs for image restoration", Journal of Mathematical Imaging and Vision, 48(1):35-52, 2014. Preliminary Version at arXiv:1112.2904, and accompanying slides. [CoupledPDEs]

  • V. B. S. Prasath, D. Vorotnikov. "Weighted and well-balanced anisotropic diffusion scheme for image denoising and restoration". Nonlinear Analysis: Real World Applications, 17:33-46, 2014.
  • V. B. S. Prasath, J. M. Urbano, D. Vorotnikov. "Analysis of adaptive forward-backward diffusion flows with applications in image processing". Inverse Problems, 31, 105008 (30pp), 2015. Preprint 15-07, Department of Mathematics, University of Coimbra. [AFBD]
  • V. B. S. Prasath, J. C. Moreno. "On convergent finite difference schemes for variational - PDE based image processing". Computational and Applied Mathematics, Jan 2017. Preliminary Version at arXiv:1310.7443.
  • V. B. S. Prasath, D. Vorotnikov. "On time adaptive critical variable exponent vectorial diffusion flows and their applications in image processing I. Analysis". Nonlinear Analysis, 168:176-197, 2018. Preliminary Version at arXiv:1603.06337. [VarEx]
I organized the Mini-Symposium on Analysis of PDEs from Image processing at the SIAM Conference on Analysis of Partial Differential Equations 2013 Conference, Lake Buena Vista, FL, USA.
II. Variational Methods, Regularization Techniques
In this direction the primary focus is to regularize ill-posed problems arising in image processing, computer vision, and machine learning. Total variation, total generalized variation, higher order total variation, l1 optimization, elastic net, sparse representation, convex, non-convex regularization, optimization, energy minimization, and corresponding numerical schemes are major thrust areas.

Project pages:
1. Regularization: MTTV, MAC, CMAC, PIDTGV, SIMREN, Gradfit, M2AC, Modseg, CBseg,
                           Fusion, OmniReg, TVzoo, L0z, Cartoon, Featurefit, REPAIR, Super, OCT (coming soon)
2. Total variation:  VTV-denoise, Decomposition, AdaptiveTV (coming soon)

Selected publications:
  • V. B. S. Prasath, A. Singh. "A hybrid convex variational model for image restoration". Applied Mathematics and Computation, 215(10):3655-3664, 2010.
  • V. B. S. Prasath. "A well-posed multiscale regularization scheme for digital image denoising". International Journal of Applied Mathematics and Computer Science, 21(4):769-777, 2011.
  • V. B. S. Prasath, D. Vorotnikov, R. Pelapur, Shani Jose, G. Seetharaman, K. Palaniappan. "Multiscale Tikhonov-total variation image restoration using spatially varying edge coherence exponent". IEEE Transactions on Image Processing, 24(12):5220-5235, 2015. [MTTV]
  • J. C. Moreno, V. B. S. Prasath, J. C. Neves. "Color image processing by vectorial
    total variation with gradient channels coupling". Inverse Problems and Imaging, 10(2):461-497, 2016. [VTV-denoise]
  • J. C. Moreno, V. B. S. Prasath, D. Vorotnikov, H. Proenca, K. Palaniappan. "Adaptive diffusion constrained total variation scheme with application to cartoon + texture + edge image decomposition". Revised, 2018. [Decomposition]
  • J. C. Moreno, V. B. S. Prasath. "Coupled multiphase active contours". Submitted, 2018. [CMAC]


III. Bio-medical Signal/Image/Video/Data Processing and Analysis
Application of signal processing, image processing and computer vision techniques to biomedical (MRI, CT, PET, SPECT, OCT, X-ray, DEXA, Ultrasound, Wireless Capsule Endoscopy, Colonoscopy, Histopathology, Confocal, Fluorescence Microscopy, Mammography, Cryo-EM, cDNA Microarray images, laryngeal high-speed videos, EEG, ECG) data. Image enhancement, noise removal, compression of endoscopic videos, image segmentation based on active contours, shape based (Shape from Shading, Shape from Motion) approaches for endoscopic images. Machine learning, deep learning for biomedical image analysis. Bioinformatics, visualization and interpretation of medical data. Segmentation and quantitative image analysis for magnetic resonance, histopathological, fluorescence microscopy images. E-health, telemedicine, m-health related data processing. Computational neuroscience, transcranial direct current stimulation (tDCS), fMRI analysis.

Project pages:
1. Endoscopy       : MucosaSeg, 3D-SfS, Stamping, Illumination, Polyps, Bleeding, Distortion,
                            Stereo, Registration,
Compression
, Summary, Polypseg, Quality, Celiac,
                            Tumor, UlcerArcEndos, Colonopolyps (coming soon)  
2. Histopathology : StromaSeg, NucleiSeg, Glioma, Mitosis, Analysis (coming soon)
3. MRI                 : MAC, MSP, Skullstrip, Symmetry, SIMMER, Bleeds, Denoising,
                             iSPi (coming soon)
4. Microscopy       : Denoising, Segmentation, Analysis, Confocal, IIF-HEp2, Retinal
                             Cryo-EM, HEp-2z, Deconvolution (coming soon)
5. tDCS               : Brief history, Plasticity, Adverse, Electrodes, Safety (coming soon)
6. Mammography : Segmentation, Enhancement, Registration (coming soon)
7. Misc                : Telemedicine, e-Health, m-Health (coming soon)

Selected publications:
  • I. N. Figueiredo, S. Prasath, Y.-H. R. Tsai, P. N. Figueiredo. "Automatic detection and segmentation of colonic polyps in wireless capsule images", CAM Report 10-65, Department of Mathematics, University of California Los Angeles (UCLA), 2010.

  • P. N. Figueiredo, I. N. Figueiredo, S. Prasath and R. Tsai. "Automatic polyp detection in PillCam COLON 2 capsule images and videos: Preliminary feasibility report". Diagnostic and Therapeutic Endoscopy, Vol. 2011, Article ID 182435, 16pp, 2011.
  • J. C. Moreno, V. B. S. Prasath, H. Proenca, K. Palaniappan. "Fast and globally convex multiphase active contours for brain MRI segmentation". Computer Vision and Image Understanding, 125:237-250, 2014. [MAC]

  • P. Kalavathi, V. B. S. Prasath. "Automatic segmentation of cerebral hemispheres in MR human head scans". International Journal of Imaging Systems and Technology - Neuroimaging and Brain Mapping, 26(1):15-23, 2016. [MSP]
  • P. Kalavathi, V. B. S. Prasath. "Methods on skull stripping of MRI head scan images - A review". Journal of Digital Imaging, 29(3):365-397, 2016. [Skullstrip]
  • V. B. S. Prasath, Y. M. Kassim, Z. A. Oraibi, J.-B. Guiriec, A. Hafiane, K. Palaniappan. "HEp-2 cell classification and segmentation using motif texture patterns and spatial features with random forests". International Contests on Pattern Recognition Techniques for Indirect Immunofluorescence Images Analysis, International Conference on Pattern Recognition (ICPR), Cancun, Mexico, Dec 2016. Proc. IEEE, pp. 90-95. [IIF-HEp2]
  • V. B. S. Prasath. "Polyp detection and segmentation from video capsule endoscopy: A review". Journal of Imaging, 3(1), 2017. Preliminary Version at arXiv:1609.01915 [Polyps]


IV. Remote Sensing, Other Image Processing/Computer Vision Problems and Non-Imaging Domains
Image speckle denoising, segmentation for SAR, PolSAR images. Road network extraction from aerial imagery. Wavelets, Shearlets for image processing. Regression analysis, Robust M-estimators, Discontinuity adaptive smoothing schemes and Kernel smoothing. Image and data fusion, multi-focus fusion, multi-sensor fusion, sensor networks. Biometrics - ocular, periocular, fingerprint, iris, retina, face, palm print. Multi-view geometry, shape from X, segmentation, optical flow, mosaicing, blending, registration, point cloud processing, large scale 3D reconstruction for full motion video (FMV), wide area motion imagery (WAMI), video surveillance, summarization, event detection. DTM/DEM, edge detection, super-resolution, deblocking, decompression, saliency detection, watermarking, steganography, Kinect depth data processing, local binary patterns, registration, video data analysis. Feature analysis, deep learning for image processing and computer vision problems. Sensor networks with emphasize on visual sensors, internet of things (IoT), affective computing (emotion recognition from image data).

Project pages:    
1. Remote Sensing: Shadows, STLLT, PolSARSeg, Clouds, Roads, WAMI  (coming soon)
2. Biometrics        : Periocular, V-sign, Veil, Fingerprint, Iris (coming soon)
3. Image quality   : MSID, BriCho (coming soon)
4. Misc                 : Splineseg, CSANG, LOHI, SSTEdges, STEAD, RC-BA, GeLaDA, Weld, LSS3D, P3D, Entrans, Fish, Traffic signs (coming soon)

Selected publications:
  • V. B. S. Prasath, A. Singh. "Multichannel image restoration using combined channel information and robust M-estimator approach", International Journal of Tomography and Statistics, 12(F10):9-22, 2010.
  • V. B. S. Prasath, O. Haddad. "Radar shadow detection in SAR images using DEM and projections", Journal Applied Remote Sensing, 8(1), 083628, 2014. Preliminary Version at arXiv:1309.1830, and accompanying datasets. [Shadows]
  • J. C. Moreno, V. B. S. Prasath, G. Santos, H. Proença. "Robust periocular recognition by fusing sparse representations of color and geometry information". Journal of Signal Processing Systems. 82(3):403-417, 2016. [Periocular]
  • H. Aliakbarpour, V. B. S. Prasath, K. Palaniappan, G. Seetharaman, J. Dias. "Heterogeneous multi-view information fusion: Review of 3-D reconstruction methods and a new registration with uncertainty modeling". IEEE Access, 4(1):8264-8285, 2016.
  • H. Aliakbarpour, J. F. Ferreira, V. B. S. Prasath, K. Palaniappan, G. Seetharaman, J. Dias. "A probabilistic framework for 3D reconstruction using heterogeneous sensors". IEEE Sensors Journal, 17(9):2640-2641, 2017.



To be updated soon with more projects! meantime you can take a look at other conference papers and abstracts. For a year based listing of publications see my publications page.
See also the Publication List with abstract and bibtex at CiVA Lab website.