OKWW filter for poisson noise removal in low-light condition digital image

Sari, Suhaila; Chia, Yi-Wei; Mohd, MA; Taujuddin, Nik Shahidah Afifi; Ibrahim, Nabilah; Roslan, Hazli

doi:10.1109/icsipa.2017.8120632

Cited by 2 publications

(6 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The estimated noise level which value is less than 0.01 is the image with low and medium Poisson noise. The value 0.01 is the lower boundary of high Poisson noise value that determine by the previous study [4]. Hence, the value of 0.01 is used to differentiate the images into low and medium Poisson noise and high Poisson noise in this research.…”

Section: Methodsmentioning

confidence: 89%

“…The noise estimation denoising technique developed by combining Patch-based Noise Level Estimator for noise estimation with the OTSU WIE-WATH Filter [4] and OTSU KU-WIE-WATH Filter [4] to eliminate the Poisson noise effectively in real application. The noise level of input image will be estimated by using Patchbased Noise Level Estimator method.…”

Section: Methodsmentioning

confidence: 99%

“…OTSU WIE-WATH Filter [4] is the combination of Otsu Threshold, Wavelet Threshold and Wiener Filter. This method is well to reduce noise in smooth region of noisy image while preserving the texture region of noisy image.…”

Section: Otsu Wie-wath Filtermentioning

confidence: 99%

“…OTSU KU-WIE-WATH Filter [4] is developed through the combination of Otsu Threshold, Kuwahara Filter, Wavelet Threshold and Wiener Filter. This proposed method will be able to reduce noise in smooth and texture regions of high level noise image.…”

Section: Otsu Ku-wie-wath Filtermentioning

confidence: 99%

“…Bilateral Filter, Median Filter, Maximum Filter and Minimum Filter) are known to be effective in preserving edges in a much better way than linear models but slower since they are usually computationally expensive [3]. OTSU WIE-WATH Filter and OTSU KU-WIE-WATH Filter [4] that proposed recently also improve the performance of eliminated the Poisson noise in an effective way. The filter allows the noisy pixels in the dark regions to be removed while preserving the texture regions to avoid over smoothing of test images.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Noise Level Based Denoising Technique Utilizing Patch- Based Noise Level Estimator for Low-Light Condition Surveillance Image

Sari¹,

Lin²,

Roslan³

et al. 2018

IJET

View full text Add to dashboard Cite

Digital Image Processing is a method to obtain image or to take out useful details or feature from image. The noise will cause the results of error in the image acquisition process. Generation of higher noise levels in the low light condition environment will often result in oversmoothed edges and textures during the denoising process because of lower signal levels in the image. Thus, this study goal is to improve denoising techniques for Poisson noise removal in low light condition for surveillance images. The Patch-Based Noise Level Estimator is designed to estimate the noise level of noisy image. The noisy image then fed to either OTSU WIE-WATH Filter or OTSU KU-WIE-WATH Filter automatically based on the noise level of image. The OTSU WIE-WATH Filter is used for low and medium Poisson noise removal while OTSU KU-WIE-WATH Filter is used mainly for high Poisson noise removal. The proposed denoising technique performances are analyzed with other existing denoising techniques in terms of Mean Absolute Error (MAE), computational time and visual effect inspection. The results verified that proposed technique is effective in removing different level Poisson noise in low light condition surveillance images.

show abstract

Section: Methodsmentioning

confidence: 89%

Section: Methodsmentioning

confidence: 99%

Section: Otsu Wie-wath Filtermentioning

confidence: 99%

Section: Otsu Ku-wie-wath Filtermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Noise Level Based Denoising Technique Utilizing Patch- Based Noise Level Estimator for Low-Light Condition Surveillance Image

Sari¹,

Lin²,

Roslan³

et al. 2018

IJET

View full text Add to dashboard Cite

show abstract

In-situ 3D shape measurement system for a high-temperature object in a plasma wind tunnel via DMD-projection laser structured light and adaptive speckle filtering

Liu¹,

Yang²,

Xiao³

et al. 2022

Meas. Sci. Technol.

View full text Add to dashboard Cite

Evaluation of object 3D shape change during ablation in wind tunnel test is critical for optimization of thermal protection system. However, strong thermal radiation and harsh environment bring challenges to the traditional measurement methods. A single camera DMD-projector structured laser light system is proposed for in-situ 3D shape measurement in wind tunnel test. A customized Digital Micro-Mirror Device (DMD) combined with laser source is devised for projecting concentrated full-field high-power structured light stripes. To filter laser speckle noise in projected chessboard images for model calibration, an auto-window Kuwahara adaptive filter is put forward. 3D shape of a blunt-head cylinder was in-situ measured in a plasma wind tunnel which maximum temperature reached 1950℃. Diameter reconstruction error was within 0.85% (0.17/20.03mm). With projected laser light and multi-step filters, ablation process of front face of a dome-top cylinder at 1950℃ was clearly observed at a long working distance over 1.5m.

show abstract

OKWW filter for poisson noise removal in low-light condition digital image

Cited by 2 publications

References 9 publications

Noise Level Based Denoising Technique Utilizing Patch- Based Noise Level Estimator for Low-Light Condition Surveillance Image

Noise Level Based Denoising Technique Utilizing Patch- Based Noise Level Estimator for Low-Light Condition Surveillance Image

In-situ 3D shape measurement system for a high-temperature object in a plasma wind tunnel via DMD-projection laser structured light and adaptive speckle filtering

Contact Info

Product

Resources

About