Name
Abstract | ||
|---|---|---|
A binary coding based feature extraction (BCFE) method is proposed in this paper. In the BCFE method, the spectral signature of each pixel of hyperspectral image is partitioned into some equal segments. Then, the weighted mean of spectral bands in each segment is considered as an extracted feature. BCFE uses a new method for calculation of weights. In BCFE, the binary codes of class means are obtained. Then, the information contained in the binary values and the edges of class means is used for calculation of weight in each band. The experimental results on three real hyperspectral images show the better performance of BCFE compared to some popular and state-of-the-art feature extraction methods, from the accuracy and computation time point of views, in a small sample size situation. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.ins.2016.01.032 | Information Sciences |
Keywords | Field | DocType |
Binary coding,Feature extraction,Classification,High dimensional data,Small sample size situation | Clustering high-dimensional data,Pattern recognition,Binary code,Feature extraction,Hyperspectral imaging,Artificial intelligence,Pixel,Spectral bands,Spectral signature,Machine learning,Mathematics,Binary number | Journal |
Volume | Issue | ISSN |
342 | C | 0020-0255 |
Citations | PageRank | References |
7 | 0.44 | 20 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Imani | 1 | 61 | 8.65 |
| Hassan Ghassemian | 2 | 396 | 34.04 |