scholarly journals NDVI COMPUTATION OF LISS III IMAGES USING QGIS

2021 ◽  
Vol 9 (1) ◽  
pp. 1451-1454
Author(s):  
Vijayalakshmi V, D Mahesh Kumar, S C Prasanna Kumar, Thejaswini P.
Keyword(s):  
Feature Detection ◽  
Mean Shift ◽  
Principal Component ◽  
Local Binary Patterns ◽  
Critical Issue ◽  
Hyperspectral Images ◽  
Multispectral Images ◽  
Multispectral Imagery ◽  
Mean Shift Algorithm ◽  
Liss Iii

Feature Selection and Extraction is a very significant and mandatory part in the domain of image processing. After the relevant preprocessing operations, the relevant features have to be extracted using suitable algorithms. In multispectral imagery, the features are identified and extracted  based on the applications and objectives of the analysis such as color, texture, brightness, intensity etc. Some of the prominent algorithms used for feature extraction are mean shift algorithm, Principal Component transformation, Wavelet based Transformation, Local Binary Patterns etc. Texture based feature detection and extraction is the most prominent method adopted which involves multispectral images.  With respect to hyperspectral images, dimensionality is a critical issue to be dealt appropriately.

Automatic vertebra segmentation based on graph cut and mean shift algorithm

2011 ◽  
Vol 31 (3) ◽  
pp. 760-762
Author(s):  
Ji LIU ◽  
Xiao-dong KANG ◽  
Fu-cang JIA
Keyword(s):  
Mean Shift ◽  
Graph Cut ◽  
Mean Shift Algorithm

The mean shift algorithm and its relation to kernel regression

2016 ◽  
Vol 348 ◽  
pp. 198-208 ◽  
Author(s):  
Youness Aliyari Ghassabeh ◽  
Frank Rudzicz
Keyword(s):  
Mean Shift ◽  
Kernel Regression ◽  
Mean Shift Algorithm ◽  
The Mean

Video Vehicle Tracking Based on Improved Mean-Shift Algorithm

2011 ◽  
Vol 179-180 ◽  
pp. 1408-1411
Author(s):  
Wei Bin Chen ◽  
Xin Zhang ◽  
Su Qin Luo
Keyword(s):  
Clustering Algorithm ◽  
Mean Shift ◽  
Vehicle Tracking ◽  
Absolute Difference ◽  
Mean Shift Algorithm ◽  
Invariant Moments ◽  
Mean Shift Clustering ◽  
Video Frames ◽  
Detection Technology ◽  
Background Area

An improved Mean-Shift-based Video vehicle tracking algorithm was proposed and which can improve the real-time and accuracy of the vehicle detection technology in the application. First, it eliminates the disturbance from unrelated background by mathematical morphology operation between a traffic image and the mask of fixed background area .Then the image sequences are simulated by absolute difference of adaptive threshold for detecting latent target. At last, clusters video frames with similar characteristics which are regarded of the invariant moments vectors by Mean Shift clustering algorithm. Experimental results shown that the improved algorithm has advantages of reducing king region of vehicle matching and vehicle complete occlusion.

scholarly journals Hyperspectral monitoring of fructose content in marzipan

2018 ◽  
Vol 14 (s1) ◽  
pp. 79-88
Author(s):  
Katalin Badak-Kerti ◽  
Szabina Németh ◽  
Andreas Zitek ◽  
Ferenc Firtha
Keyword(s):  
Principal Component Analysis ◽  
Spatial Distribution ◽  
Spectral Properties ◽  
Oil Content ◽  
Sugar Content ◽  
Principal Component ◽  
Reducing Sugar ◽  
Hyperspectral Data ◽  
Hyperspectral Images ◽  
Analysis Technique

In our research marzipan samples of different sugar to almond paste ratios (1:1, 2:1, 3:1) were stored at 17 °C. Reducing sugar content was measured by analytical method, texture analysis was done by penetrometry, electric characteristics were measured by conductometry and hyperspectral images were taken 6–8 times during the 16 days of storage. For statistical analyses (discriminant analysis, principal component analysis) SPSS program was used. According to our findings with the hyperspectral analysis technique, it is possible to identify how long the samples were stored (after production), and to which class (ratio of sugar to almond) the sample belonged. The main wavelengths which gave the best discrimination results among the days of storage were between 960 and 1100 nm. The type of the marzipan was easy to distinguish with the hyperspectral data; the biggest differences were observed at 1200 and 1400 nm, which are connected to the first overtone of C-H bound, therefore correlate with the oil content. The spatial distribution of penetrometric, electric and spectral properties were also characteristic to fructose content. The fructose content of marzipan is difficult to measure by usual optical ways (polarimetry, spectroscopy), but since fructose is hygroscopic, the spatial distribution of spectral properties can be characteristic.

A dual-mode mean-shift algorithm

2008 ◽  
Author(s):  
Shih-Yu Chiu ◽  
Jia-Rui Zhang ◽  
Leu-Shing Lan
Keyword(s):  
Mean Shift ◽  
Dual Mode ◽  
Mean Shift Algorithm

scholarly journals Pendugaan Intensitas Serangan Penyakit BLB (Bacterial Leaf Blight) pada Tanaman Padi melalui Pendekatan Citra Multispektral

2020 ◽  
Vol 8 (2) ◽  
pp. 338
Author(s):  
Gusti Bagus Eka Chandra ◽  
I Made Anom S. Wijaya ◽  
Yohanes Setiyo
Keyword(s):  
Technology Development ◽  
Leaf Blight ◽  
Multispectral Image ◽  
Bacterial Leaf Blight ◽  
Estimation Accuracy ◽  
Multispectral Images ◽  
Multispectral Imagery ◽  
Rice Plants ◽  
Red Edge ◽  
Disease Attack

ABSTRAK Penyakit Bacterial Leaf Blight (BLB) merupakan salah satu penyakit yang berbahaya bagi tanaman padi. Penyakit ini bisa menyerang di setiap fase pertumbuhan. Perhitungan intensitas serangan penyakit BLB saat ini masih dilakukan secara manual. Diperlukan pengembangan teknologi dalam pendugaan intensitas serangan penyakit BLB melalui citra multispektral. Penelitian ini bertujuan untuk (1) untuk mendapatkan nilai korelasi terbaik antara intensitas serangan penyakit BLB dengan parameter citra multispektral (2) Untuk mendapatkan persamaan pendugaan intensitas serangan penyakit BLB berdasarkan pendekatan citra multispektral. Drone DJI Inspire 1 dengan kamera multispektral digunakan untuk menangkap gambar petak padi. Pengolahan data citra multispektral menggunakan Agisoft Photoscan dan software QGIS 3.8. Berdasarkan dari hasil akuisisi, citra multispektral menghasilkan citra band red, NIR, green, red edge, RGB yang kemudian diolah menjadi transformasi citra NDVI, EVI, dan NDRE. Dari ketiga parameter citra multispektral, nilai NDVI memiliki tingkat korelasi yang lebih kuat dengan koefisien determinasi sebesar 97,5% dan menghasilkan persamaan linier sebagai berikut y = -419,6 + 169,3. Dalam perhitungan nilai eror parameter NDVI memilikinilai eror paling rendah dibandingkan parameter EVI dan NDRE yaitu sebesar 4,64% dengan akurasi pendugaan 95,36%. Citra multispektral dapat digunakan dalam pendugaan intensitas serangan penyakit BLB pada tanaman padi karena menghasilkan nilai korelasi yang sangat kuat, dan akurasi pendugaan yang tinggi dengan nilai eror yang rendah tidak melebihi 10%. ABSTRACT  Bacterial Leaf Blight (BLB) is a disease that is dangerous for rice plants. This disease can attack in every phase of growth. Calculation of BLB disease attack intensity is currently still used manually method. Technology development is needed in estimating the intensity of BLB disease through multispectral imagery. This study aims (1) to get the best correlation value between the intensity of BLB disease attack with multispectral image parameters (2) to get the equation for estimating the intensity of BLB based on multispectral images parameter. Drone DJI Inspire 1 with a multispectral camera is used to captured the paddy field. The captured images was processed using Agisoft Photoscan and QGIS 3.8 software. Based on the results of the acquisition, multispectral images produce red, NIR, green, red edge, RGB band images which were then transformed into NDVI, EVI, and NDRE images. Of the three multispectral image parameters, NDVI values ??have a stronger correlation level with a determination coefficient of 97.5% and produce the following linear equation y = -419.6 + 169.3. In calculating the NDVI parameter error value has the lowest error value compared to the EVI and NDRE parameters which is 4.64% with an accuracy estimate of 95.36%. Multispectral imagery can be used in estimating the intensity of BLB disease attacks in rice plants because it produces a very strong correlation value, and high estimation accuracy with a low error value does not exceed 10%.

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