• Matlab
  • Simulink
  • NS3
  • OMNET++
  • COOJA
  • CONTIKI OS
  • NS2

Feature Selection for Hyperspectral Image via Learning

Spectral-spatial feature combination for hyperspectral image analysis has become an important research topic in hyperspectral remote sensing applications. A simple and straightforward way to integrate spectral-spatial features is to concatenate heterogeneous features into a long vector. Then, the dimensionality reduction techniques, i.e., feature selection, are applied before subsequent utilizations. However, such representation can introduce redundancy and noise. Moreover, traditional single-feature selection methods treat different features equally and ignore their complementary properties. As a result, the performance of subsequent tasks, i.e., classification, would drop down.

In this paper, we propose a novel approach to integrate the spectral-spatial features based on the concatenating strategy, termed discriminative sparse multimodal learning for feature selection (DSML-FS). In the proposed method, joint structured sparsity regularizations are used to exploit the intrinsic data structure and relationships among different features. Discriminative least squares regression is applied to enlarge the distance between classes. Therefore, the weight matrix incorporating the information of feature wise and individual properties is automatically learned for spectral-spatial feature selection. We develop an alternative iterative algorithm to solve the nonlinear optimization problem in DSML-FS with global convergence. We systematically evaluate the proposed algorithm on three available hyperspectral data sets, and the encouraging experimental results demonstrate the effectiveness of DSML-FS.

Related Matlab Project Titles:

Subscribe Our Youtube Channel

You can Watch all Subjects Matlab & Simulink latest Innovative Project Results

Watch The Results

Our services

We want to support Uncompromise Matlab service for all your Requirements Our Reseachers and Technical team keep update the technology for all subjects ,We assure We Meet out Your Needs.

Our Services

  • Matlab Research Paper Help
  • Matlab assignment help
  • Matlab Project Help
  • Matlab Homework Help
  • Simulink assignment help
  • Simulink Project Help
  • Simulink Homework Help
  • Matlab Research Paper Help
  • NS3 Research Paper Help
  • Omnet++ Research Paper Help

Our Benefits

  • Customised Matlab Assignments
  • Global Assignment Knowledge
  • Best Assignment Writers
  • Certified Matlab Trainers
  • Experienced Matlab Developers
  • Over 400k+ Satisfied Students
  • Ontime support
  • Best Price Guarantee
  • Plagiarism Free Work
  • Correct Citations

Delivery Materials

Unlimited support we offer you

For better understanding purpose we provide following Materials for all Kind of Research & Assignment & Homework service.

  • Programs
  • Designs
  • Simulations
  • Results
  • Graphs
  • Result snapshot
  • Video Tutorial
  • Instructions Profile
  • Sofware Install Guide
  • Execution Guidance
  • Explanations
  • Implement Plan

Matlab Projects

Matlab projects innovators has laid our steps in all dimension related to math works.Our concern support matlab projects for more than 10 years.Many Research scholars are benefited by our matlab projects service.We are trusted institution who supplies matlab projects for many universities and colleges.

Reasons to choose Matlab Projects .org???

Our Service are widely utilized by Research centers.More than 5000+ Projects & Thesis has been provided by us to Students & Research Scholars. All current mathworks software versions are being updated by us.

Our concern has provided the required solution for all the above mention technical problems required by clients with best Customer Support.

  • Novel Idea
  • Ontime Delivery
  • Best Prices
  • Unique Work

Simulation Projects Workflow

Embedded Projects Workflow