東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Development and assessment of advanc...

Cakir, Halil I.

FindBook

Google Book

Amazon

博客來

Development and assessment of advanced data fusion algorithms for remotely sensed data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Development and assessment of advanced data fusion algorithms for remotely sensed data./
作者:	Cakir, Halil I.
面頁冊數:	160 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 5479.
Contained By:	Dissertation Abstracts International65-11B.
標題:	Agriculture, Forestry and Wildlife. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3154185
ISBN:	0496146823

Development and assessment of advanced data fusion algorithms for remotely sensed data.
Cakir, Halil I.

Development and assessment of advanced data fusion algorithms for remotely sensed data. - 160 p.

Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 5479.

Thesis (Ph.D.)--North Carolina State University, 2004.

The general objective of this study is to develop and implement data fusion methodologies for remotely sensed imagery. Utilization of multisource and multidate data sources in remote sensing studies has gained popularity with recent technological advances. From increases in spatial resolution to better change detection, data fusion processes have become an important part of remote sensing. Broadly defined, data fusion is a necessary step or component of most remote sensing studies. This research combines three studies in which new data fusion methodologies are developed and implemented for remotely sensed data.

ISBN: 0496146823Subjects--Topical Terms:

783690
Agriculture, Forestry and Wildlife.

Development and assessment of advanced data fusion algorithms for remotely sensed data.
LDR:03408nmm 2200349 4500 001 1849114
005 20051209075318.5
008 130614s2004 eng d
020 $a 0496146823
035 $a (UnM)AAI3154185
035 $a AAI3154185
040 $a UnM $c UnM
100 1 $a Cakir, Halil I. $3 1937093
245 1 0 $a Development and assessment of advanced data fusion algorithms for remotely sensed data.
300 $a 160 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-11, Section: B, page: 5479.
500 $a Chair: Siamak Khorram.
502 $a Thesis (Ph.D.)--North Carolina State University, 2004.
520 $a The general objective of this study is to develop and implement data fusion methodologies for remotely sensed imagery. Utilization of multisource and multidate data sources in remote sensing studies has gained popularity with recent technological advances. From increases in spatial resolution to better change detection, data fusion processes have become an important part of remote sensing. Broadly defined, data fusion is a necessary step or component of most remote sensing studies. This research combines three studies in which new data fusion methodologies are developed and implemented for remotely sensed data.
520 $a In the first study, utilization of a multiresolution approach is explored. Information gathered from the multiresolution analysis of multispectral and panchromatic images is used to increase the spatial resolution of multispectral imagery with minimal loss in the spectral integrity of the original input data. 30-meter Landsat 7 multispectral imagery is fused with 15-meter same-satellite panchromatic imagery to increase the spatial resolution of the former.
520 $a In the second study, a multivariate analysis procedure called correspondence analysis (CA) is utilized to fuse 4-meter IKONOS multispectral imagery with 1-meter IKONOS panchromatic imagery. In this method, the last component of a correspondence analysis image is replaced with 1-meter panchromatic imagery before the CA image is transformed back to the original image space. An analysis of the fused image shows that this technique keeps most of the original image variance while distortion remains minimal.
520 $a In the last study, CA is utilized to improve change detection accuracy when detecting changes between two dates of imagery. Before and after Landsat images of Raleigh, North Carolina are transformed into component space individually using CA. Then, an image-differencing method is applied to the individual components. It is concluded that using the first CA component with image differencing drastically improves the detection of change between two dates.
520 $a Overall, these studies provide new methodologies for fusing the multisource and multidate images. Two methods to increase the spatial resolution of remotely sensed data and one method to perform change detection are proposed. All the proposed methodologies are an improvement over present commonly used techniques within their respective application areas.
590 $a School code: 0155.
650 4 $a Agriculture, Forestry and Wildlife. $3 783690
650 4 $a Computer Science. $3 626642
650 4 $a Environmental Sciences. $3 676987
650 4 $a Remote Sensing. $3 1018559
690 $a 0478
690 $a 0984
690 $a 0768
690 $a 0799
710 2 0 $a North Carolina State University. $3 1018772
773 0 $t Dissertation Abstracts International $g 65-11B.
790 1 0 $a Khorram, Siamak, $e advisor
790 $a 0155
791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3154185