MARC details
| 000 -LEADER |
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| fixed length control field |
03585ntm a2200277 a 4500 |
| 001 - CONTROL NUMBER |
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| control field |
vtls000101365 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
KUKTEM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251117113341.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
170928t2017 my a f am 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0001253(Local) |
| 039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE] |
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| Level of rules in bibliographic description |
201905271348 |
| Level of effort used to assign nonsubject heading access points |
atie |
| Level of effort used to assign subject headings |
201710030929 |
| Level of effort used to assign classification |
fateeha |
| -- |
201709281139 |
| -- |
fateeha |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UMP |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
FSKKP .S26 2017 r Thesis |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Santoso, Ardhi Wicaksono |
| 245 10 - TITLE STATEMENT |
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| Title |
Fuzzy-based frost filter for speckle noise reduction of Synthetic Aperture Radar (SAR) image / |
| Statement of responsibility, etc. |
Ardhi Wicaksono Santoso |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Kuantan, Pahang : |
| Name of publisher, distributor, etc. |
UMP, |
| Date of publication, distribution, etc. |
2017 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xiv, 117 p. : |
| Other physical details |
ill. (some col.) ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 500 ## - GENERAL NOTE |
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| General note |
Faculty of Computer Systems & Software Engineering |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (Master of Science) -- Universiti Malaysia Pahang – 2017 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Bibliography : p. 100-104 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
The Synthetic Aperture Radar (SAR) image is a high-resolution image and is less influenced by weather conditions either day or night compared to the optical image. SAR image, because of its advantages, is becoming more popular than the optical image in the remote sensing area for earth observation study. However, the speckle noise that occurs in the SAR image causes difficulties in image interpretation, and speckle noise reduction process has become necessary before of the usage of SAR image. The ideal speckle filter has the capability of reducing speckle noise without losing the information and preserving its texture. This study proposes the use of speckle noise filter that as nearly possible to meet those criteria. This research has investigated the performance of existing filter, which was Frost, Lee, Kuan, and Median, and had applied it to ALOS-PALSAR images with homogeneous and heterogeneous earth area surfaces in Kuantan, Pahang, Malaysia. Filtered image is measured and evaluated using image quality parameters to show the performance of the filters in reducing speckle noise and preserving the texture. The parameter used for filters evaluation performances are Equivalent Number of Looks (ENL), Speckle Index (SI), Mean, Standard Deviation and Variance. The experiment results showed that Frost filter has better results compared to others and has been selected as the qualified existing filter. The Frost filter was modified by applying the fuzzy approach which was aimed at eliminating speckle noise while maintaining texture. There are four combinations of proposed filter, which are Frost-ATMAV, Frost-ATMED, Frost-TMAV, and Frost-TMED combination. Based on the results of comparison and evaluation of the filters, Frost-TMAV combination has been selected as the best-proposed filter. It had improved the performance of Frost filters for each parameter's measurement; it showed the improvement value of 19.47% for ENL, 8.48% for SI, 2.56% for mean, 6.15% for standard deviation and 2.00% for a variance, applied into homogeneous areas of ALOS-PALSAR images. While when used with heterogeneous areas, it improved 9.54% for ENL, 4.41% for SI, 3.03% for mean, 1.51% for standard deviation and 2.96% for the variance. It has been verified that the Frost-TMAV could be used for ALOS-PALSAR data pre-processing, which means that this filter can produce good-quality images based on parameters used when compared with other filters. |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
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| Corporate name or jurisdiction name as entry element |
Faculty of Computer Systems & Software Engineering |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Universities and Colleges |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Theses |