PROJECTS ON IMAGE PROCESSING USING MATLAB
Image processing is defined as a technique that is used to enhance the original images from satellites,artifacts,pictures taken in day to day life cameras,etc.Projects on Image Processing using Matlab is used in compression and data hiding projects.Two ways used for image processing they are
- Digital image processing
Analog way used for hard copies like printouts and photographs.image processing uses many filters.filters can be broad band or narrow band.A broad band filter allows many colors for instance the entire red or green area of a spectrum.
2015 IEEE PROJECTS ON IMAGE PROCESSING USING MATLAB
- COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.
- A Novel Range Grating Lobe Suppression Method Based on the Stepped-Frequency SAR Image.
- Sparse Unmixing of Hyperspectral Data Using Spectral A Priori Information.
- A Novel Feature Selection Approach Based on FODPSO and SVM.
- A Pansharpening Method Based on the Sparse Representation of Injected Details.
- Block Adjustment for Satellite Imagery Based on the Strip Constraint.
- Bayesian Blind Separation and Deconvolution of Dynamic Image Sequences Using Sparsity Priors.
- Local-Manifold-Learning-Based Graph Construction for Semisupervised Hyperspectral Image Classification.
- Learning Understandable Neural Networks With Nonnegative Weight Constraints.
- Two-Tier Tissue Decomposition for Histopathological Image Representation and Classification.
- Feature Matching With an Adaptive Optical Sensor in a Ground Target Tracking System.
- Classification of Hyperspectral Image Based on Sparse Representation in Tangent Space.
- Spectral Unmixing of Hyperspectral Imagery Using Multilayer NMF.
- A New Sparsity-Based Band Selection Method for Target Detection of Hyperspectral Image.
- An Adaptive Pixon Extraction Technique for Multispectral/Hyperspectral Image Classification.
Projects on Image Processing using MATLAB is used in following sectors.
- Visualization apps including image viewer and video viewer.
- Image analysis, including morphology,statistics,segmentation and measurement.
- Image transforms, which includes FFT,Radon,DCT and fan-beam projection.
- Image enhancement, debugging and filtering.
- Large image work flows which includes block processing ,multiresolution display and tilling.
- Multicore and GPU- enabled functions and C-code generation support.
The process of extracting meaningful information from an image is called image analysis. Image analysis consists of image matching and comparison,medical diagnosis from an image and image segmentation.In data hiding projects one face is hidden from another file.There are many ways to hide the data for ex ,taking mean or median values of neighboring pixels.
Projects on Image processing using Matlab uses following math :
Probability and statistics.
Differential equations (ODEs and PDEs).
Engineering students who wants to gather information and skills in edge image technique can make use of image processing.using image processing we can find the damage caused by earthquakes.
Image processing toolbox has image blurring algorithm includes blind,wiener,lucky-Richardson and regularized filter re convolution optical transfer functions and conversions between point-spread.
Object boundaries in an image can be identified using edge-detection algorithms.These algorithms include the Roberts,canny,prewitt,sobel and laplacian of Gaussian methods.true weak edges without any noise can be detected using canny method.in optical character recognition system,edge detection process is used.
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