000			03349nam a2200397 4500
005			20260818114756.0
008			310898 th eng
035			_a.b10030074
099		9	_aAIT Thesis no. CS-91-25
100	1		_aPan, Rui
245	1	2	_aA fuzzy pixel decomposition approach in the classification of remotely sensed data
260			_aBangkok : _bAsian Institute of Technology, _c1991
300			_a85 p.
490	1		_aThesis ; _vno. CS-91-25
500			_aA thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Enginering and Technology
502			_aThesis (M.Eng.) - Asian Institute of Technology, 1991
520			_aIn conventional remote sensing classification, most classification results are represented in a one-pixel-one-class mapping in which a pixel is an indivisible minimum unit no matter whether it is class mixture pixel or not, which greatly and always limits the improvement of classification and boundary accuracies. This work describes a new classification approach of using fuzzy pixel decomposition algorithm to deal with the class mixture problem, where each pixel is represented as a fuzzy pixel and divided into non-fuzzy sub-pixels. The algorithm consists of two major steps: Pixel membership grade analysis, and Pixel decomposition, in which fuzzy set theory is applied for representing land cover membership grade for each pixel, neural network and statistical approaches are used for analyzing pixel class membership grade. Afterwards, each pixel is decomposed into sub-pixels, and the membership grades of neighboring pixels are used for identifying the-position of each sub-pixel. An idea of distance in neural network is presented, and a method of selecting minimum training data is also described in this work. Evaluations were made among conventional, neural network and pixel decomposition classifiers. The results of classifying TM and MOS-1 images in the areas of Thailand were presented and their accuracies were analyzed which showed the improvement in both classification and boundary accuracies as well as thematic map. The studies show that class mixture in a pixel can be identified, and the fuzzy pixel decomposition ·algorithm is a useful tool in improving final classification output of remotely sensed data.
650		0	_aLand use _xRemote sensing
650		0	_aImage processing _xDigital techniques
700	1		_aHosomura, Tsukasa, _eChairperson
700	0		_aVilas Wuwongse, _eExamination Committee
700	1		_aZhao, Ming, _eExamination committee
710	2		_aGovernment of Japan, _eScholarship donor
810	2		_aAsian Institute of Technology. _tThesis ; _vno. CS-91-25
856			_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B17347
907			_a.b10030074 _bmnait _cx
902			_a240409
998			_b2 _c951012 _dm _ea _fx _g2
945			_lmnait
945			_lmnarc
942			_c22
942			_c40
909			_aBarcode : 30050120677017 _bCREATED : 2013-11-22 _cRECORD # : i12749035 _dLPATRON : 0 _eLCHKIN : - _f# RENEWALS : 0 _g# OVERDUE : 0 _hIUSE3 : 0 _iTOT CHKOUT : 0 _jTOT RENEW : 0
909			_aBarcode : 30050120372742 _bCREATED : 2016-08-06 _cRECORD # : i13026501 _dLPATRON : 0 _eLCHKIN : - _f# RENEWALS : 0 _g# OVERDUE : 0 _hIUSE3 : 0 _iTOT CHKOUT : 0 _jTOT RENEW : 0
999			_c48500 _d48500