Nearest Neighbor Value Interpolation

Rukundo, Olivier; Cao, Hanqiang

doi:10.14569/ijacsa.2012.030405

Cited by 90 publications

(50 citation statements)

References 1 publication

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“…Olivier and C. Hanquing [14] has presented a new interpolation algorithm which is based on the nearest neighbor interpolation algorithm. But it uses the nearest values rather than distance to calculate the missing pixels.…”

Section: A Kaushik and M Guptamentioning

confidence: 99%

An Improved Image CompressionDecompression Technique Using Block Truncation and Wavelets

Mander¹,

Jindal²

2017

IJIGSP

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Abstract-In the modern world, digital images play a vital role in a number of applications such as medical field, aerospace and satellite imaging, underwater imaging, etc. These applications use and produce a large number of digital images. Also, these images need to be stored and transmitted for various purposes. Thus, to overcome this problem of storage while transmitting these images, a process is used, namely, compression. The paper focuses on a compression technique known as Block Truncation Coding (BTC) as it helps in reducing the size of the image so that it takes less space in memory and easy to transmit. Thus, BTC is used to compress grayscale images. After compression, Discrete Wavelet Transform (DWT) with spline interpolation is applied to reconstruct the images. The process is suggested in order to view the changed pixels of images after compression of two images. The wavelets and interpolations provide enhanced compressed images that follow the steps for its encoding and decoding processes. The performance of the proposed method is measured by calculating the PSNR values and on comparing the proposed technique with the existing ones, it has been discovered that the proposed method outperforms the most common existing techniques and provides 49% better results in comparison with existing techniques.

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Section: A Kaushik and M Guptamentioning

confidence: 99%

An Improved Image CompressionDecompression Technique Using Block Truncation and Wavelets

Mander¹,

Jindal²

2017

IJIGSP

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“…W badaniach przyjęto domyślne wartości parametrów (ArcGIS, funkcja LAS Dataset to Raster) -parametr potęgi równy 2 i obszar poszukiwań ograniczony do rozmiaru najmniejszej komórki generowanego modelu [12,13]. ○ Metoda najbliższego sąsiada -każda komórka wynikowego modelu przyjmuje wartość wysokości punktu, znajdującego się najbliżej centrum komórki [13,14]. ○ Triangulacja z interpolacją metodą liniową i naturalnego sąsiada -obie metody opierają się na utworzeniu modelu wektorowego TIN (ang.…”

Section: Metodyka Badańunclassified

Application of Selected Methods of Generating Regular Terrain Models from Airborne Laser Scanning for Environmental Research

Rozpondek

Wancisiewicz

2017

Eng. Prot. Environ.

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The accuracy of models representing the shape of the land surface is important in environmental studies. Accurate model can be used to detect even small changes in the landform and landuse, as well as to develop a spatial model of water and soil pollution. Due to the fact that environmental studies are carried out on diversified areas in terms of landuse, this study indicated the appropriate methods for generating Digital Terrain Model (DTM) and Digital Surface Model (DSM). Both of them can be used in processes and analyzes research. Those analyzes mainly take into account the formation of the Earth's surface in the context of hydrological, geomorphological and biological modeling. The example of practical use of hydrological modeling is a ISOK project, which goal is to reduce the danger and minimize losses caused by the floods. The main aim of this study was to select the appropriate method of generating regular models from airborne laser scanning. The data on which analysis was performed, were obtained for the area of Cracow city within the project ISOK. To achieve this goal, four methods available in ArcGIS, were selected: nearest neighbour, inverse distance weighted, triangulation with linear interpolation and triangulation with natural neighbour interpolation. Additionally several different sizes of the cell of regular model were selected: 0.125, 0.25, 0.5, 1, 2.5, 5 m. Each generated model has been studied in terms of a accuracy (Gaussian statistical model was used). Firstly the analysis was made for digital terrain model and digital surface model for one archive module of point cloud. For this stage, 48 models were generated. After that, the area of analysis was expanded. Because of similar results obtained by both triangulations methods in the first stage, only the method of triangulation with linear interpolation was studied. In the second stage of research, 54 models were generated for other archive modules of point cloud. The results of the two stages were compatible. It has been noticed that the nearest neighbour method is the most accurate for generating Digital Surface Models.

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“…Different techniques can be applied as interpolators; Polynomial interpolation, Multivariate interpolation, Bilinear interpolation, Bi-cubic spline interpolation, K-Nearest-neighbor interpolation (KNN), Inverse distance weighting (IDW) Interpolation, quadratic interpolation, B-spline interpolation, Lagrange interpolation, Gaussian interpolation, among other techniques [5][6][7]. Interpolation techniques are well expressed in the application of image processing, data mining, artificial neural networks, as well as other variant applications.…”

Section: Background On Interpolationmentioning

confidence: 99%

“…The distance between the center point ‫ݐݑ(‬ 5 ) and its neighbors were calculated using the Euclidean distance function as in (1). C. A weight sequence was calculated for the expanded vector by using Hinton & Roweis weight function (6). The exponential function included within (6) will concentrate on the center point as it has the biggest effect on the predicted point.…”

Section: Icdes 2016mentioning

confidence: 99%

“…B. The expanded grid was used similarly (as with EwEf method) to generate a weight sequence with Hinton & Roweis weight function described in (6), and Euclidean distance function as in (1). C. The weight sequence then was used to calibrate (IP) measurements by (8), the data set resulted by applying (8) is considered the calibrated corrosion measurements.…”

Section: Icdes 2016mentioning

confidence: 99%

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Comparative Calibration of Corrosion Measurements Using K-Nearest Neighbour Based Techniques

Hamed

Shafie

Mustaffa

et al. 2016

MATEC Web of Conferences

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Abstract. Every measuring equipment or inspection tool is known to have its own accuracy, which may affect the reliability of its measurements. This includes oil and gas pipeline corrosion defects measurements. The inspection tolerance occurred in the measurements should be treated carefully for each equipment to prevent misinterpretation of the data which could lead to incorrect assessment. This paper presents a comparison between two K-Nearest Neighbour (KNN) interpolation techniques used to calibrate corrosion measurements collected by Magnetic Flux Leakage Intelligent Pig (MFL-IP) with the readings of Ultrasonic Testing (UT) scan device. The comparison has relied on the position of the interpolators, the weight sequence, and the error in the final enhanced metrics compared to the original measurements. Both techniques have the potential to calibrate and enhance IP measurements, with relative advantage for one technique in reducing over fitting problem. This enhancement will be used to improve the integrity assessment report that depends on the disturbed corrosion metrics of oil and gas pipelines, to decide whether the pipeline is fit for service or needs certain maintenance.

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Nearest Neighbor Value Interpolation

Cited by 90 publications

References 1 publication

An Improved Image CompressionDecompression Technique Using Block Truncation and Wavelets

An Improved Image CompressionDecompression Technique Using Block Truncation and Wavelets

Application of Selected Methods of Generating Regular Terrain Models from Airborne Laser Scanning for Environmental Research

Comparative Calibration of Corrosion Measurements Using K-Nearest Neighbour Based Techniques

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