Out-of-focus blur image restoration using the Akamatsu transform

Karungaru, Stephen; Sugizaki, Masakazu; Fukumi, Minoru; Mitsukura, Yasue; Akamatsu, Norio

doi:10.1109/iecon.2009.5415072

Cited by 4 publications

(29 citation statements)

References 5 publications

(5 reference statements)

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“…El kernel utilizado en forma matricial sobre el eje es (ecuación 8): (8) Y sobre el eje es (ecuación 9): (9) En estas matrices la fila o la columna con ceros es la responsable de dividir la imagen. La figura 7 muestra el resultado del filtro para la imagen de prueba.…”

Section: Filtro Sobel-prewittunclassified

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Identificación visual sobre sistema embebido para navegación robótica autónoma

Ariza

2014

Ingenium Rev. fac. ing.

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Resumen ResumenEste artículo de investigación ataca el problema de la navegación robótica autónoma basada en sistemas de visión artificial en tiempo real. Como una primera aproximación a un sistema de visión artificial que permita la navegación del robot, se ha desacoplado el módulo sensor e implementado como una unidad independiente sobre un pequeño robot diferencial. Sobre él, se han realizado estudios básicos de navegación por identificación visual de landmarks (marcas especiales) en un ambiente desconocido. Los estudios de desempeño, realizados tanto a través de simulación como por evaluación directa sobre prototipos en laboratorio, demuestran la eficacia de las estructuras propuestas, tanto del hardware de identificación en tiempo real como de la estrategia básica de navegación considerada para su evaluación. Palabras claveAndroid, imágenes, procesamiento en tiempo real, sistema embebido.

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Section: Filtro Sobel-prewittunclassified

“…Los sistemas de imagen en tiempo real normalmente procesan una cadena de imágenes digitales, las analizan, y controlan alguna parte del sistema de acuerdo al resultado de este análisis. Esto es de particular importancia en aplicaciones de control [8], [9].…”

Section: I Introducción Introducciónunclassified

Identificación visual sobre sistema embebido para navegación robótica autónoma

Ariza

2014

Ingenium Rev. fac. ing.

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“…Research [15] correcting or restoring images' blur using the Akamatsu Transform method. Akamatsu Transform is a technique Norio Akamatsu proposed to create differential and integral signals from the given original signals.…”

Section: Introductionmentioning

confidence: 99%

“…In a study [16], the blurred image restoration used the Bi-directional Akamatsu Transform method. This method is a research development of the Akamatsu Transform method [15]. The development of this method is that this method performs the Akamatsu Transform horizontally or in the direction of the X-axis and vertically or in the direction of the Y-axis.…”

Section: Introductionmentioning

confidence: 99%

Remove Blur Image Using Bi-Directional Akamatsu Transform and Discrete Wavelet Transform

Andono

Sari²

2022

SJI

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Purpose: Image is an imitation of everything that can be materialized, and digital images are taken using a machine. Although digital image capture uses machines, digital images are not free from interference. Image restoration is needed to restore the quality of the damaged image.Methods: Bi-directional Akamatsu Transform is proven to have an effective performance in reducing blur in images. Meanwhile, Discrete Wavelet Transform has been widely used in digital image processing research. We had been investigated the image restoration method by combining Bi-directional Akamatsu Transform and Discrete Wavelet Transform. Bi-directional Akamatsu Transform applied in Low-Low (LL) sub-band is the Discrete Wavelet Transform decomposition image most similar to the original image before decomposing. In this study, there are still shortcomings, including the determination of the values of N, up_enh, and down_enh, which are still manual. Manually setting the three values makes the Bi-directional Akamatsu Transform method not get the best results. With the use of machine learning methods can get better restoration results. Further testing is also needed for a more diverse and robust blur. The image data has a resolution of 256x256, 512x512, and 1024x1024. The image will be directly converted to a grey-scale image. The converted image will be given an attack model: average blur, gaussian blur, and motion blur. The image that has been attacked will apply two restoration methods: the proposed method and the Bi-direction Akatamatsu Transform. These two restoration images will then be compared using PSNR.Result: The average PSNR value from the restoration of the proposed method is 0.1446 higher than the average PSNR value from the restoration of the Bi-directional Akamatsu Transform method. When we compare it with the average PSNR value of the Akamatsu Transform restoration method, the average PSNR of the proposed method is 0.2084.Value: The combination of DWT and akamatsu transform results produce good PSNR values even though they have gone through the blurring method in image restoration.

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“…To test the quality of restoration method will be given various image noise such as Gaussian noise, salt & pepper, and blur. The result of the restoration will be calculated by the PSNR and compared with the method contained in the research Karungaru et al [5] and Megha P et al [6].…”

Section: Introductionmentioning

confidence: 99%

Joint method using Akamatsu and discrete wavelet transform for image restoration

Akbar

Setiadi

2020

ACI

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Current technology makes it easy for humans to take an image and convert it to digital content, but sometimes there is additional noise in the image so it looks damaged. The damage that often occurs, like blurring and excessive noise in digital images, can certainly affect the meaning and quality of the image. Image restoration is a process used to restore the image to its original state before the image damage occurs. In this research, we proposed an image restoration method by combining Wavelet transformation and Akamatsu transformation. Based on previous research Akamatsu's transformation only works well on blurred images. In order not to focus solely on blurry images, Akamatsu's transformation will be applied based on Wavelet transformations on high-low (HL), low-high (LH), and high-high (HH) subunits. The result of the proposed method will be comparable with the previous methods. PSNR is used as a measure of image quality restoration. Based on the results the proposed method can improve the quality of the restoration on image noise, such as Gaussian, salt and pepper, and also works well on blurred images. The average increase is around 2 dB based on the PSNR calculation.

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Out-of-focus blur image restoration using the Akamatsu transform

Cited by 4 publications

References 5 publications

Identificación visual sobre sistema embebido para navegación robótica autónoma

Identificación visual sobre sistema embebido para navegación robótica autónoma

Remove Blur Image Using Bi-Directional Akamatsu Transform and Discrete Wavelet Transform

Joint method using Akamatsu and discrete wavelet transform for image restoration

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