Projects

IMAGE PROCESSING BASED PROJECTS



  1. An Efficient Phase and Object Estimation Scheme for Phase-Diversity Time Series Data
  2. A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
  3. LCD Motion Blur Reduction: A Signal Processing Approach
  4. A Lossless Compression Scheme for Bayer Color Filter Array Images
  5. Optimal Sensor Array Configuration in Remote Image Formation
  6. Image Classification Using Correlation Tensor Analysis
  7. Orthogonal Rotation-Invariant Moments for Digital Image Processing
  8. Generalized Flooding and Multicue PDE-Based Image Segmentation
  9. Maximum Likelihood Wavelet Density Estimation With Applications to Image and Shape Matching
  10. Weighted Adaptive Lifting-Based Wavelet Transform for Image Coding
  11. A Run-Based Two-Scan Labeling Algorithm
  12. Using Spanning Graphs for Efficient Image Registration
  13. Continuous Sampling in Mutual-Information Registration
  14. Universal Impulse Noise Filter Based on Genetic Programming
  15. Active Learning Methods for Interactive Image Retrieval
  16. Analysis and Compensation of Rolling Shutter Effect
  17. Automatic Active Model Initialization via Poisson Inverse Gradient
  18. FIR Filter Banks for Hexagonal Data Processing
  19. Wavelet Feature Selection for Image Classification
  20. Robust Control-Based Object Tracking
  21. Binary Partition Trees for Object Detection
  22. A Sparsity-Enforcing Method for Learning Face Features
  23. A Fast Multilevel Algorithm for Wavelet-Regularized Image Restoration
  24. Mode-kn Factor Analysis for Image Ensembles
  25. Preferential Image Segmentation Using Trees of Shapes
  26. A Shearlet Approach to Edge Analysis and Detection
  27. Study on Huber Fractal Image Compression
  28. Spherical Coding Algorithm for Wavelet Image Compression
  29. Multiple Description Coding With Prediction Compensation
  30. Signal and Image Approximation Using Interval Wavelet Transform
  31. Face Verification With Balanced Thresholds
  32. Optimal Signature Design for Spread-Spectrum Steganography



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