Feature extraction using Mel frequency cepstral coefficients for hyperspectral image classification

被引：4

作者：

Liu, Delian ^{[1
]}

Wang, Xiaorui ^{[1
]}

Zhang, Jianqi ^{[1
]}

Huang, Xi ^{[1
]}

机构：

[1] Xidian Univ, Sch Tech Phys, Xian 710071, Shaanxi, Peoples R China

来源：

APPLIED OPTICS | 2010年 / 49卷 / 14期

基金：

中国国家自然科学基金;

关键词：

REMOTE-SENSING IMAGES; ALGORITHM;

D O I：

10.1364/AO.49.002670

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

The Mel frequency cepstral coefficient (MFCC) model, which is widely used in speech detection and recognition, is introduced to extract features from hyperspectral image data. The similarities and differences between speech signals and spectral image data are compared and analyzed. The standard MFCC model is then improved to suit the characteristics of spectral image data by reintroducing the discarded phase information. Finally, the proposed model is applied to two real hyperspectral subimages. Experimental results show that the MFCC feature is sensitive and discriminative among reflectance spectra. It can be used as an effective feature extraction method for hyperspectral image classification. (C) 2010 Optical Society of America

引用

页码：2670 / 2675

页数：6

共 50 条

[1] Palmprint recognition based on Mel frequency Cepstral coefficients feature extraction
Fahmy, Maged M. M.
[J]. AIN SHAMS ENGINEERING JOURNAL, 2010, 1 (01) : 39 - 47
[2] MEL-CEPSTRAL METHODS FOR IMAGE FEATURE EXTRACTION
Cakir, Serdar
Cetin, A. Enis
[J]. 2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, 2010, : 4577 - 4580
[3] Mel-cepstral feature extraction methods for image representation
Cakir, Serdar
Cetin, A. Enis
[J]. OPTICAL ENGINEERING, 2010, 49 (09)
[4] Breathing site classification via joint mel frequency cepstral coefficients and gammatone frequency cepstral coefficients approach
Zhang, Jiarui
Ling, Bingo Wing-Kuen
[J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (02) : 3623 - 3634
[5] Fusion of Linear and Mel Frequency Cepstral Coefficients for Automatic Classification of Reptiles
Noda, Juan J.
Travieso, Carlos M.
Sanchez-Rodriguez, David
[J]. APPLIED SCIENCES-BASEL, 2017, 7 (02):
[6] Fingerprint Recognition Using Mel-Frequency Cepstral Coefficients
Hashad F.G.
Halim T.M.
Diab S.M.
Sallam B.M.
El-Samie F.E.A.
[J]. Pattern Recognition and Image Analysis, 2010, 20 (03) : 360 - 369
[7] A Wavelet Packet and Mel-Frequency Cepstral Coefficients-Based Feature Extraction Method for Speaker Identification
Turner, Claude
Joseph, Anthony
[J]. COMPLEX ADAPTIVE SYSTEMS, 2015, 2015, 61 : 416 - 421
[8] Classification of Heart Sounds using Linear Prediction Coefficients and Mel-Frequency Cepstral Coefficients as Acoustic Features
Narvaez, Pedro
Vera, Katerine
Bedoya, Nhikolas
Percybrooks, Winston S.
[J]. 2017 IEEE COLOMBIAN CONFERENCE ON COMMUNICATIONS AND COMPUTING (COLCOM), 2017,
[9] Feature Extraction for Hyperspectral Image Classification
Uddin, M. P.
Mamun, M. A.
Hossain, M. A.
[J]. 2017 IEEE REGION 10 HUMANITARIAN TECHNOLOGY CONFERENCE (R10-HTC), 2017, : 379 - 382
[10] Feature Extraction of some Quranic Recitation using Mel-Frequency Cepstral Coeficients (MFCC)
Bezoui, Mouaz
Elmoutaouakkil, Abdelmajid
Beni-hssane, Abderrahim
[J]. PROCEEDINGS OF 2016 5TH INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS), 2016, : 127 - 131

← 1 2 3 4 5 →