Application of Interpolation Image by using Bi-Cubic Algorithm

Abdullah, Dahlan; Fajriana, F; Maryana, M; Rosnita, Lidya; Siahaan, Andysah Putera Utama; Rahim, Robbi; Harliana, Putri; Harmayani, Harmayani; Ginting, Zainuddin; Erliana, Cut Ita; Irwansyah, Defi; Zulmiardi, Z; Khaddafi, Muammar; Milanie, Feby; Aspan, Henry; Huda, Ismul; Saddhono, Kundharu; Mulyaningsih, Indrya; Moonti, Roy Marthen; Parwito,; Djanggih, Hardianto; Amalia, Ainna; Winarno, Edy; Hadikurniawati, Wiwien

doi:10.1088/1742-6596/1114/1/012066

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…Different approaches have been used for the spatio-temporal interpolation, but only a few applied BSS and STK, without providing comparisons [ 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 ]. The least studied is BSS interpolation [ 85 , 106 ]. Therefore, deeper investigations must be carried out on various data series to assess the performances of BSS and STK.…”

Section: Resultsmentioning

confidence: 99%

Downscaling MERRA-2 Reanalysis PM2.5 Series over the Arabian Gulf by Inverse Distance Weighting, Bicubic Spline Smoothing, and Spatio-Temporal Kriging

Saliba,

Bărbulescu

2024

Toxics

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This study offers a detailed analysis of the fine particulate matter (PM2.5) series in the Arabian Gulf zone, employing three interpolation models, Inverse Distance Weighting (IDW), Bicubic Spline Smoothing (BSS) and Spatio-Temporal Kriging (STK). Unique advancements include the use of complete temporal records in IDW, the management of edge effects in S with synthetic buffer points, and the application of STK to detrended data residuals. The results indicated that the BBS, particularly adept at handling boundary conditions, significantly outperformed the other methods. Compared to IDW, the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) decreased by 21%, 15%, and 21%, respectively, in BSS. Compared to STK, MAE, RMSE, and MAPE were lower with around 60%, 61%, and 58%, respectively in BSS. These findings underscore the efficacy of the BSS method in spatial interpolation for environmental monitoring, contributing to enhanced PM2.5 analysis and public health management in the region.

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Section: Resultsmentioning

confidence: 99%

Downscaling MERRA-2 Reanalysis PM2.5 Series over the Arabian Gulf by Inverse Distance Weighting, Bicubic Spline Smoothing, and Spatio-Temporal Kriging

Saliba,

Bărbulescu

2024

Toxics

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“…We also change the parallel structure to a more lightweight series structure to reduce the number of parameters in the feature extraction process. Additionally, we change the nearest neighbor interpolation [20] used in the original model to Bi-Cubic interpolation [21] and adopt a multi-scale training approach.…”

Section: Plos Onementioning

confidence: 99%

YOLO-plum: A high precision and real-time improved algorithm for plum recognition

Niu,

Lu,

Liang

et al. 2023

PLoS ONE

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Real-time, rapid, accurate, and non-destructive batch testing of fruit growth state is crucial for improving economic benefits. However, for plums, environmental variability, multi-scale, occlusion, overlapping of leaves or fruits pose significant challenges to accurate and complete labeling using mainstream algorithms like YOLOv5. In this study, we established the first artificial dataset of plums and used deep learning to improve target detection. Our improved YOLOv5 algorithm achieved more accurate and rapid batch identification of immature plums, resulting in improved quality and economic benefits. The YOLOv5-plum algorithm showed 91.65% recognition accuracy for immature plums after our algorithmic improvements. Currently, the YOLOv5-plum algorithm has demonstrated significant advantages in detecting unripe plums and can potentially be applied to other unripe fruits in the future.

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“…Other techniques used for interpolation like Bell interpolation (Abdullah et al, 2018), and Hermite interpolation (Seta et al, 2009) were mainly focused on the speed constraint. Indeed, Bell interpolation provides a smooth image with continuous contours.…”

Section: Interpolation Algorithms Overviewmentioning

confidence: 99%

An improvement of efficient nonlinear color image interpolator: Theory and FPGA implementation

Boudabbous¹,

Graja²

2023

Int. j. adv. appl. sci.

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In this paper, a new proposal for a nonlinear edge-preserving interpolator and hardware implementation is presented. As a new idea for a color image interpolator, our proposal is focusing on the interpolated pixel and we tried to adjust it in order to have better quality. To evaluate the effectiveness of the proposed idea for preserving images, we implemented it using different color images and we evaluated using different evaluation measurements. Then, we compared our new proposal with the traditional nonlinear Edge preserving interpolator. The obtained results confirm that our proposed Edge preserving is better than the old interpolator. It also demonstrates consistent image quality performance among a variety of images. The hardware implementation based on FPGA shows that we are able to gain image quality without increasing the size of the circuit once implemented in hardware. We show that our proposed interpolator for Edge preserving improves considerably the image quality and represents a fast solution when implemented in hardware. Despite a small increase in FPGA resources, we obtain an average improvement of the image quality of about 35.75% using the NCD metric.

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Application of Interpolation Image by using Bi-Cubic Algorithm

Cited by 9 publications

References 7 publications

Downscaling MERRA-2 Reanalysis PM2.5 Series over the Arabian Gulf by Inverse Distance Weighting, Bicubic Spline Smoothing, and Spatio-Temporal Kriging

Downscaling MERRA-2 Reanalysis PM2.5 Series over the Arabian Gulf by Inverse Distance Weighting, Bicubic Spline Smoothing, and Spatio-Temporal Kriging

YOLO-plum: A high precision and real-time improved algorithm for plum recognition

An improvement of efficient nonlinear color image interpolator: Theory and FPGA implementation

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