Trending: Anna University 8th Sem Results April 2014 May/June 2014 Time Table/ Internal Marks Calculate CGPA Online SSLC Results 2014 12th Result 2014

Test Footer 1

Monday, February 10, 2014

RS7201 DIGITAL IMAGE PROCESSING Syllabus | Anna University M.Tech Remote Sensing Second Semester Syllabus Regulation 2013

Latest: TNEA 2014 Engineering Application Status, Counselling Date, Rank List

Anna University Syllabus - Anna University M.Tech Syllabus

RS7201 DIGITAL IMAGE PROCESSING Syllabus | Anna University M.Tech Remote Sensing Second Semester Syllabus Regulation 2013. Below is the Anna University 2013 Regulation Syllabus for 2nd Semester for M.Tech Remotes Sensing, Textbooks, Reference books, Exam portions, Question Bank, Previous year question papers, Model question papers, Class notes, Important 2 marks, 8 marks, 16 marks topics.
It is applicable for all students admitted in the Academic year 2013-2014 onwards for all its Affiliated institutions in Tamil Nadu.


 The objective of the course is to describe about the procedure of satellite data acquisition and analysis.
UNIT I FUNDAMENTALS 9 Satellite systems and data – acquisition - storage - orbits – Data formats –Data products - Image display systems - future missions - Elements of visual perception – Image sampling and quantization - Basic relationship between pixels. UNIT II SENSOR AND DATA MODEL 9 Sensor model – Resolutions - pixel characters - Image formation – Histogram -Types- Uni-variate & multi-variate image statistics – spatial statistics – Geometric and radiometric correction - noise models. UNIT III IMAGE ENHANCEMENTS 9 Spectral signatures – Image characteristics, feature space scatterogram- point, local and regional operation – contrast, spatial feature and multi image manipulation techniques - Fourier transform - principle component analysis - Optimal Rotation Transformation – scale-space transform, wavelet transform.
UNIT IV INFORMATION EXTRACTION 9 Image registration and ortho rectification – resampling - multi-image fusion - Baye‟s Theorem – parametric Classification and training sites - Supervised, Unsupervised and Hybrid classifiers – other Non - parametric classifiers - sub-pixel and super-pixel classification – Hyper-spectral image analysis – Accuracy assessment. UNIT V IMAGE ANALYSIS 9 Pattern recognition - boundary detection and representation - textural and contextual analysis - decision concepts: Fuzzy sets - evidential reasoning - Expert system - Artificial Neural Network. TOTAL: 45 PERIODS OUTCOME: On completion of this course, the student shall be able to
 Get familiarized about various image enhancement and image processing techniques
1. John R. Jensen, Introductory Digital Image Processing: A Remote Sensing Perspective, 2nd Edition, 1995.
2. Robert Shcowebgerdt, Remote sensing models & methods for image processing, III edition, 2004.
3. John A.Richards, Springer – Verlag, Remate Sensing Digital Image Analysis 1999.
4. Digital Image Processing (3rd Edition) Rafael C. Gonzalez, Richard E. Woods Prentice Hall, 2007.
5. W.G.Rees - Physical Principles of Remote Sensing, Cambridge University Press, 2nd edition, 2001.

No comments:

Post a Comment

Any doubt ??? Just throw it Here...