PRINCIPAL INVESTIGATOR: (Mentor)

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• PRINCIPAL INVESTIGATOR (Mentor)
• Dr.Srinivasan Vathsal
• Professor and Head, Dept of EEE, Dean RD,
• JBIET, Yenkapally, Moinabad, RR Dist.
• svathsal_at_gmail.com
• 07702299775
• CO-PRINCIPAL INVESTIGATORS (Mentee)
• Dr.Syed Amjad Ali
• Professor, Department of ECE
• Sy.No32, Lords Institute of Engineering and
  Technology,
• Himayath sagar, Hyderabad.
• Syedamjadali.lords_at_gmail.com

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PROPOSAL SUMMARY

• Real time imaging is the rapid acquisition and
  manipulation of information from a scanning probe
  by electronic circuits to enable images to be
  produced on TV screens almost instantaneously.
• Medical imaging is used for clinical diagnosis
  and computer aided surgery.
• We have chosen medical tomographic imaging area
  to denoise computerized tomographic images and
  video, visual quality enhancement using
  enhancement techniques, compress it and transmit
  simultaneously, while real time imaging. Medical
  imaging is used for clinical diagnosis and
  computer aided surgery.

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• We propose to design and develop the algorithms
  and techniques in the following areas,
• Identification of noise in the CT imaging (image
  and video)
• Noise variance estimation techniques for specific
  noise.
• Denoise using advanced wavelet and multiwavelet
  techniques
• Quality enhancement technique for image and
  video
• Compression using advanced compression
  techniques.
• Transmission techniques for transmission of
  images and video.

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• There is a need for transmission of CT images in
  telemedicine for quick diagnosis and remedial
  action at very short duration of time.
• Simultaneously transmission of information helps
  the medical practioners in taking instant
  decision for treatment, as it is concerned to
  health of a patient.
• This proposal can be treated as a good project of
  national interest for instant help in medical
  treatment for life saving under Mobile-Health
  Care.

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TECHNICAL DESCRIPTION

• Technical objective
• This project is proposed in the national interest
  for speedy medical treatment for the patient as
  and when approaches, as it is related to precious
  life of a human being.
• To obtain real time computerized tomographic
  imaging, denoising, quality enhancement,
  compressing and transmitting the images and the
  video to any part of the world for better
  medical diagnosis, opinion and the instant
  treatment.

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• Relation to prior work
• This project is an extension of our Ph.D research
  work, wherein, we carried out the research work
  for denoising the tomographic images using
  wavelets7, 9-11, 16,17, 19, 20, 22,
  26 and multiwavelet techniques4, 8, 13,
  27, 28 for decomposition.
• Developed univariate and multivariate
  thresholding techniques3 for denoising.
• Developed a modified visual quality enhancement
  techniques of images
• i) using modified Canny based edge detection
• algorithms12.
• ii)using modified morphological thinning
  operation.
• Developed lossy and lossless compression
  techniques18 for compression of an image. We
  have applied the above techniques for the still
  and natural MRI images.

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• To still images, we have added additive white
  Gaussian noise at different noise levels and
  denoised using window based multiwavelet
  transformation14, 23 and thresholding
  techniques.
• We developed genetic algorithm based window
  selection24 for the optimization of windowing
  technique.
• We have also developed estimation techniques1,
  2, 15, 21, 29, 30 to estimate the noise
  content in natural MRI images of a patient, and
  then applied denoising techniques using wavelets,
  multiwavelets and thresholding.
• As an extension work, we would like to estimate
  the noise while real time imaging (image video)
  and then apply advanced denoising techniques
  using wavelets and multiwavelet transformations
  for decomposing and then thresholding to remove
  noise, then apply advanced compression
  techniques, and use high speed transmission at
  fast rate, every thing simultaneously while
  imaging.

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Research challenges

• Design and development of algorithms for
  identifying the type of noise in natural image
  and video.
• Design and development of algorithm for efficient
  noise variance estimation techniques while
  imaging natural images and video.
• Design and development of algorithms for
  denoising image and video using advanced fast
  wavelet and multiwavelet transforms for
  decomposition and reconstruction.
• Design and development of algorithms for advanced
  thresholding techniques.
• Design and development of algorithms for advanced
  lossless compression techniques.
• Design and development of algorithms compatible
  to safe and fast transmission without loss of
  data, for the transmission of huge data in the
  form of images and videos, simultaneously while
  imaging.

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• The above proposed techniques can be grouped into
  two categories 
• Design and development of algorithms for the
  identification, estimation, denoising and
  compression techniques.
• Design and development of algorithms for
  transmission of images and videos.
• Innovative aspect of proposed work
• Every aspect of above proposed algorithm will be
  new and innovative work.

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• We identify noise in real time image by comparing
  the noise with the predefined noise model.
• Then estimate noise variance by using methods
  like Median Absolute Deviation.
• In order to denoise an image, we propose modified
  Discrete Wavelet Transform and modified CL
  Multiwavelet Transform by constructing the
  multifilter coefficients and implementing in the
  transformation techniques.

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• For compression, we propose Set Partition in
  Heirarchical Tree (SPIHT) and Discrete Cosine
  Transform.
• For Quality enhancement of an image, we propose
  modified Canny based edge detection algorithm.
• For removal of noise from video signals, we use
  Digital video broadcasting-cable (DVB-C). It
  improves the Bit Error Rate (BER).

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EDUCATIONAL PLAN

• Educational activity
•  
• Development of course
•  
• Design a complete course for digital image
  processing related to the techniques used in this
  research based project such as,
• Theoretical and practical approach of
  identification of various types of noise.
• Theoretical and practical approach of noise
  variance estimation techniques.
• Theoretical and practical approach of
  constructing wavelets and multiwavelet
  techniques.
• Theoretical and practical approach of developing
  univariate and multivariate thresholding
  techniques.
• Theoretical and practical approach of compression
  and decompression techniques.
• Transmission techniques.
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• Development of Laboratory
• Personal Computers.
• Matlab R2011b with complete range of Toolboxes.

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• Man power required to develop the new innovative
  algorithms for proposed work
• To hire faculty having good programming skills,
  to develop the proposed algorithms in Matlab.
• To involve M.Tech students by giving research
  oriented projects in the proposed research
  activity.
• To involve Ph.D scholars by formulating Ph.D
  research problem in the proposed research
  activity.

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COLLABORATION PLAN

•  
• Joginpally Bhaskar Institute of Engineering
  Technology, Lords Institute of Engineering
  Technology and Vidya Vikas Institute of
  Technology are at a distance of 15 Kmts from each
  other and one more mentee is at a distance of
  300 kmts.
• In order to communicate and discuss on regular
  basis, we have the facility to fix up a meeting,
  visits, for the discussion on technical problem
  as the partner institutions are nearby. we have
  good internet facility, and teleconferencing .
• It helps in frequent discussions and exchange
  views and the ideas on the proposed work.

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• OUT REACH PLAN
• In order to collect the required medical data, we
  need to approach Hospitals.
• We need help from industry for the interfacing of
  the proposed work.
• ORGANIZATIONAL ASSISTANCE
• We need help in the area of transmission of
  images and video, from Information Technology
  Research Academy (ITRA).

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• REFERENCES
•  
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• T.Freeman, Automatic estimation and
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• IEEE Transactions on Pattern Analysis and
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•  
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• vol 16, no.9, September 2007, pp.2284-2298.
•  
• 3 David L. Donoho, De-noising by
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• Information Theory, vol.41, no.3, Mar1994,
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•  
• 4 Downie.T.R., Silverman.B.W., The discrete
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•  
• 5 F.Natterer, The mathematics of computerized
  tomographyClassics-in applied

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• 6 Gabor T.Herman, Fundamentals of computerized
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• reconstruction from projections, 2nd
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•  
• 7 Gilbert Strang and Troung Nguyen, Wavelets
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• Cambridge press, Wellsley MA, First
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•  
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•  
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• Laplacian mixure model, IEEE
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• vol.56, no.12, December 2009,
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• 12 John Canny, A computational approach to
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•  
• 13 Jo Yew Tham, Lixin Shen, Seng Luan Lee, and
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•  
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• 18 Michael B.Martin and Amy E.Bell, New image
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• multiwavelet packets, IEEE Transactions
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• Transactions on Image Processing, vol.10,
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•  
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• images, IEEE Transactions on Medical
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•  
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  Collins,
• Robust Rician noise estimation for MR
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• 2010, pp.483-493.
•  
• 22 Pizurica. A., Philips. W., Lemahieu I., and
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•  
• 23 Prof.Syed Amjad Ali, Dr.Srinivasan Vathsal,
  and Dr.K.Lal Kishore,An efficient denoising
  technique for

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•  
• 25 Prof.Syed Amjad Ali, Dr.Srinivasan Vathsal,
  Dr.K.Lal Kishore, CT image denoising technique
  using GA
• aided window-based multiwavelet
  transformation and thresholding with the
  incorporation of an
• effective quality enhancement method,
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•  
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•  
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• BUDGET
• Infrastructure _________
• Personal Computers _________
• Matlab Software(R2011b) _________
• Related Toolboxes _________
• Training expenses ________
• Stationary
  ________
• Miscellaneous expenses ________
•  

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• SUPPLEMENTARY MATERIAL
• Advisory board members
• Dr.Tanuja Srivastava
• Professor, Department of Mathematics,
• IIT, Roorkee- 247667, UP, INDIA.
• 01332-85084(O), 01332-85123(R), 01332-71793(R)
•  
• Dr.Umesh Kumar,
• BARC, Trombay, Mumbai-400085.
• umeshkum_at_barc.gov.in
•  
• Dr.C.Muralidhar,
• Head, NDED, DRDL, Hyderabad-500258.
•  
• Dr.V.V.Rao,
• Principal, JBIET, Yenkapally, R.R.Dist.
•  
• Dr.G.Durga Prasad,

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• Collaborating organizations
• Joginpally Bhaskar Institute of Engineering and
  Technology.
• Lords Institute of Engineering and Technology.
• Vidya Vikas Institute of Technology.
• Narsaraopet Engineering College.