OPTIMALISASI ANALISIS DENOISING CITRA MENGGUNAKAN ALGORITMA GAUSSIAN FILTER PADA CITRA SATELITE

PRATAMA, YOGI TIARA and Sukemi, Sukemi (2019) OPTIMALISASI ANALISIS DENOISING CITRA MENGGUNAKAN ALGORITMA GAUSSIAN FILTER PADA CITRA SATELITE. Undergraduate thesis, Sriwijaya University.

[thumbnail of RAMA_56201_09011281320009.pdf] Text
RAMA_56201_09011281320009.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (2MB) | Request a copy
[thumbnail of RAMA_56201_09011281320009_TURNITIN.pdf] Text
RAMA_56201_09011281320009_TURNITIN.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (8MB) | Request a copy
[thumbnail of RAMA_56201_09011281320009_0003126604_01_front_ref.pdf]
Preview
Text
RAMA_56201_09011281320009_0003126604_01_front_ref.pdf - Accepted Version
Available under License Creative Commons Public Domain Dedication.

Download (780kB) | Preview
[thumbnail of RAMA_56201_09011281320009_0003126604_02.pdf] Text
RAMA_56201_09011281320009_0003126604_02.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (248kB) | Request a copy
[thumbnail of RAMA_56201_09011281320009_0003126604_03.pdf] Text
RAMA_56201_09011281320009_0003126604_03.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (434kB) | Request a copy
[thumbnail of RAMA_56201_09011281320009_0003126604_04.pdf] Text
RAMA_56201_09011281320009_0003126604_04.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (2MB) | Request a copy
[thumbnail of RAMA_56201_09011281320009_0003126604_04.pdf] Text
RAMA_56201_09011281320009_0003126604_04.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (2MB) | Request a copy
[thumbnail of RAMA_56201_09011281320009_0003126604_05.pdf] Text
RAMA_56201_09011281320009_0003126604_05.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (85kB) | Request a copy
[thumbnail of RAMA_56201_09011281320009_0003126604_06_REF.pdf] Text
RAMA_56201_09011281320009_0003126604_06_REF.pdf - Bibliography
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (157kB) | Request a copy
[thumbnail of RAMA_56201_09011281320009_0003126604_07_LAMP.pdf] Text
RAMA_56201_09011281320009_0003126604_07_LAMP.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Public Domain Dedication.

Download (391kB) | Request a copy

Abstract

Satellite image contains some noise or roar which can pull down a image quality, in order to fix it needs a matrix filtering using gaussian filter that is started Gaussian matrix 3x3, 5x5, 7x7, and 9x9 or higher. This study will find out a matrix on the most optimal Gaussian filter in decreasing noise by seeing MSE and PSNR value from processing image result. A filtering process used 24 data of satellite image that was produced by BMKG of Palembang and was added noise salt & pepper 10 % dan noise specklese as much as 10% for 24 satellite data. This design used static image or not in a real time, then through image processing at cropping stage, noise addition, and filtering, next was an optimalization process used a program to get MSE value, PSNR, and process time on Gaussian matriks 9x9, 90x90, dan 190x19, therefore refraction compared which matrix that was the most optimal to reduce noise on satellite image. . Satellite image that has been done a filtering process used Visual Studio C# 2010 program, the result of the testing was MSE value and PSNR which that value will be lower if Gaussian matrix that was used higher, due to the process of Gaussian filter convolution, edge pixels were ignored and did not convolute. An edge pixels value was same as early image value that has produced a filtering process was only occured in the middle of karnel, hence from the testing of 9x9, 90x90, and 190x190 matrix the most optimal was 9x9 matrix because almost the whole karnel has changed with a new pixels value.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Gaussian filter, noise, image processing, satellite, salt & pepper, speckle, PSNR
Subjects: T Technology > T Technology (General) > T10.5-11.9 Communication of technical information
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: Users 2013 not found.
Date Deposited: 23 Sep 2019 09:00
Last Modified: 23 Sep 2019 09:00
URI: http://repository.unsri.ac.id/id/eprint/8606

Actions (login required)

View Item View Item