Algorithm to estimate the degree of camera shaking and noise corruption

Byung Chul Choi, Ji Woong Choi, Moon Gi Kang

Research output: Contribution to journalConference article

Abstract

While acquiring the image, the shaking of the acquiring device or of the object seriously damages the acquired image. This phenomenon, which decreases the distinction of the image is called motion blur. In this paper, a newly defined function is introduced for finding the degree and the length of the motion blur. The domain of this function is called the Peak-trace domain. In the Peak-trace domain, the noise dominant region -for calculating the noise variance- and the signal dominant region -for extracting the degree and the length of the motion blur- are defined. Using the information of the Peak-trace in the signal dominant region, we can fastly find the direction of the motion blur with noise immunity. A new weighted least mean square method helps extracting the Peak-trace more precisely. After getting the direction of the motion blur, we can find the degree of the motion blur very fast using a one dimensional Cepstrum method. In our experiment, we could efficiently restore the damaged image using the informations we got by the above mentioned method.

Original languageEnglish
Pages (from-to)106-116
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3653
Issue numberI
Publication statusPublished - 1999 Jan 1
EventProceedings of the 1999 Visual Communications and Image Processing - San Jose, CA, USA
Duration: 1999 Jan 251999 Jan 27

Fingerprint

Motion Blur
shaking
Camera
Cameras
cameras
estimates
Trace
Estimate
Cepstrum
Least Mean Square
Experiments
immunity
Immunity
Direction compound
Damage
damage
Decrease
Experiment

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

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title = "Algorithm to estimate the degree of camera shaking and noise corruption",
abstract = "While acquiring the image, the shaking of the acquiring device or of the object seriously damages the acquired image. This phenomenon, which decreases the distinction of the image is called motion blur. In this paper, a newly defined function is introduced for finding the degree and the length of the motion blur. The domain of this function is called the Peak-trace domain. In the Peak-trace domain, the noise dominant region -for calculating the noise variance- and the signal dominant region -for extracting the degree and the length of the motion blur- are defined. Using the information of the Peak-trace in the signal dominant region, we can fastly find the direction of the motion blur with noise immunity. A new weighted least mean square method helps extracting the Peak-trace more precisely. After getting the direction of the motion blur, we can find the degree of the motion blur very fast using a one dimensional Cepstrum method. In our experiment, we could efficiently restore the damaged image using the informations we got by the above mentioned method.",
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Algorithm to estimate the degree of camera shaking and noise corruption. / Choi, Byung Chul; Choi, Ji Woong; Kang, Moon Gi.

In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 3653, No. I, 01.01.1999, p. 106-116.

Research output: Contribution to journalConference article

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AU - Choi, Ji Woong

AU - Kang, Moon Gi

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N2 - While acquiring the image, the shaking of the acquiring device or of the object seriously damages the acquired image. This phenomenon, which decreases the distinction of the image is called motion blur. In this paper, a newly defined function is introduced for finding the degree and the length of the motion blur. The domain of this function is called the Peak-trace domain. In the Peak-trace domain, the noise dominant region -for calculating the noise variance- and the signal dominant region -for extracting the degree and the length of the motion blur- are defined. Using the information of the Peak-trace in the signal dominant region, we can fastly find the direction of the motion blur with noise immunity. A new weighted least mean square method helps extracting the Peak-trace more precisely. After getting the direction of the motion blur, we can find the degree of the motion blur very fast using a one dimensional Cepstrum method. In our experiment, we could efficiently restore the damaged image using the informations we got by the above mentioned method.

AB - While acquiring the image, the shaking of the acquiring device or of the object seriously damages the acquired image. This phenomenon, which decreases the distinction of the image is called motion blur. In this paper, a newly defined function is introduced for finding the degree and the length of the motion blur. The domain of this function is called the Peak-trace domain. In the Peak-trace domain, the noise dominant region -for calculating the noise variance- and the signal dominant region -for extracting the degree and the length of the motion blur- are defined. Using the information of the Peak-trace in the signal dominant region, we can fastly find the direction of the motion blur with noise immunity. A new weighted least mean square method helps extracting the Peak-trace more precisely. After getting the direction of the motion blur, we can find the degree of the motion blur very fast using a one dimensional Cepstrum method. In our experiment, we could efficiently restore the damaged image using the informations we got by the above mentioned method.

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