Texture Measurement Through Local Pattern Quantization for SAR Image Classification

被引：2

作者：

Chakraborty, Debasish ^{[1
]}

Dutta, Dibyendu ^{[1
]}

Sharma, Jaswant Raj ^{[2
]}

机构：

[1] ISRO, RRSC East NRSC, Kolkata 700156, India

[2] ISRO, Reg Ctr NRSC, Hyderabad 500037, Andhra Pradesh, India

来源：

JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING | 2016年 / 44卷 / 03期

关键词：

Image; Texture; Pattern; SAR; Classification; RISAT-1; RISAT-2; Local pattern quantization; SEGMENTATION; AREAS;

D O I：

10.1007/s12524-015-0495-8

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

A novel local pattern based classification algorithm for SAR image is proposed in this paper. The proposed method initially quantizes homogeneous and non-homogeneous patterns within the moving window. An operator is constructed to quantize local patterns. Quantized patterns are then used for measuring texture around the central pixel within the moving window. The ISODATA algorithm is used to classify texture transformed image. The proposed classification method is robust to speckle noise, computationally simple and does not need to set any predefined parameter for classification. The validation of the method is done on RISAT-1 and RISAT-2 data.

引用

页码：471 / 477

页数：7

共 50 条

[21] Unsupervised Amplitude and Texture Classification of SAR Images With Multinomial Latent Model
Kayabol, Koray
Zerubia, Josiane
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013, 22 (02) : 561 - 572
[22] Texture image retrieval by combining local binary pattern and discontinuity binary pattern
Kumar, T. G. Subash
Nagarajan, V.
2014 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP), 2014,
[23] Local Oppugnant Color Texture Pattern for image retrieval system
Jacob, I. Jeena
Srinivasagan, K. G.
Jayapriya, K.
PATTERN RECOGNITION LETTERS, 2014, 42 : 72 - 78
[24] IMAGE SEQUENCES TEXTURE ANALYSIS BASED ON VECTOR QUANTIZATION
Bogucharskiy, S., I
Mashtalir, S., V
RADIO ELECTRONICS COMPUTER SCIENCE CONTROL, 2014, 2 : 94 - 99
[25] A STUDY ON PATTERN ENCODING OF LOCAL BINARY PATTERNS FOR TEXTURE-BASED IMAGE SEGMENTATION
Wu, Chih-Hung
Lu, Li-Wei
Li, Yao-Yu
PROCEEDINGS OF 2014 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 2, 2014, : 592 - 596
[26] Local neighborhood difference pattern: A new feature descriptor for natural and texture image retrieval
Verma, Manisha
Raman, Balasubramanian
MULTIMEDIA TOOLS AND APPLICATIONS, 2018, 77 (10) : 11843 - 11866
[27] Fast texture classification of denoised SAR image patches using GLCM on Spark
Ozcan, Caner
Ersoy, Okan
Ogul, Iskender Ulgen
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2020, 28 (01) : 182 - 195
[28] Image classification with Local Directional Decoded Ternary Pattern
El Khadiri, I.
Chahi, A.
El-merabet, Y.
Ruichek, Y.
Touahni, R.
2019 6TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT 2019), 2019, : 812 - 817
[29] Multithresholding techniques in SAR image classification
Rey, Andrea
Delrieux, Claudio
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2021, 23
[30] SAR Image Despeckling by Soft Classification
Gragnaniello, Diego
Poggi, Giovanni
Scarpa, Giuseppe
Verdoliva, Luisa
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2016, 9 (06) : 2118 - 2130

← 1 2 3 4 5 →