Medical Image Denoising Using Adaptive Threshold Based on Contourlet Transform

Satheesh, Santhosh; Prasad, K. Rajendra

doi:10.5121/acij.2011.2205

Cited by 32 publications

(21 citation statements)

References 10 publications

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“…Based on qualitative and quantitative analysis it shows that this algorithm is more efficient than the wavelet methods in image denoising particularly for removal of Gaussian noise. This method can obtain high PSNR than wavelet based denoising algorithm using MR images in the presence of AWGN [10] Rohini Mahajan proposed wavelet domain denoising for the removal of Rican noise from MR images and this method depends on the selection of threshold value which in turn predicts the efficiency of denoising method. Symlet filter (sym6) is used for denoising purpose which tends to preserve the shape of reflectance peak and smoothness value of data point [16].…”

Section: Introductionmentioning

confidence: 99%

MRI Images Techniques

Patil¹,

Raskar²

2015

International Journal of Advanced Research in Computer and Comm

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Magnetic Resonance Imaging (MRI) is beneficial and effective diagnostic tool in basic analysis, clinical investigation, and unwellness identification since it provides each chemical and physiological info regarding the tissue underneath investigation. however once noise get introduced in mister pictures, it decreases the image quality ,Image analysis and becomes tough to diagnose it accurately. A trade off between noise reduction and preservation of actual image options must build in such manner that enhance the diagnostically relevant image content. so noise reduction remains difficult task. This paper proposes wave domain denoising for removal of Rician noise from MR Image. This methodology heavily depends on alternative of threshold parameter that successively determines the potency of denoising.

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Section: Introductionmentioning

confidence: 99%

MRI Images Techniques

Patil¹,

Raskar²

2015

International Journal of Advanced Research in Computer and Comm

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“…It has only two possible values, low and high.. The corrupted pixels are set alternatively to the minimum or to the maximum value, giving the image a "salt and pepper" like appearance [3]. Unaffected pixels remain unchanged.…”

Section: Salt and Pepper Noisementioning

confidence: 99%

A Histogram based Hybrid Approach for Medical Image Denoising using Wavelet and Curvelet Transforms

Tamilselvan¹,

Murugesan²,

Vinothsaravanan³

2013

IJCA

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“…It is also mentioned that these methods can also be applied to remote sensing images. Sathish et al [8] proposed denoising technique based on contourlets and experimented with the medical images acquired by Magnetic Resonance Imaging (MRI) and claimed that it achieves higher peak signal to noise ratio (PSNR) when compared to wavelet based methods. A new approach based on cellular neural network to denoise an image was proposed in [9].…”

Section: Introductionmentioning

confidence: 99%

An Approach based on Run Length Count for Denoising the Kannada Characters

Karthik¹,

R²,

K³

2012

IJCA

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Optical Character Recognition (OCR) is one of the important fields in image processing and pattern recognition domain. OCR with high accuracy finds application in offices, banks, healthcare etc. The accuracy of the OCR is primarily dependent on the quality of the input image. So, to achieve high accuracy OCR we should provide a high quality image, which is free from different types of noises, degradation, skews etc. In this paper, we have made an attempt to remove the noise, which is present in the input image. A novel method based on run length count is proposed to denoise the images. In this approach first the noisy image is binarized. Based on the horizontal and vertical run length count, the noise in the image will be identified and eliminated. The algorithm is tested with noisy epigraphical document images, noisy printed document images. The effectiveness of the algorithm is verified with images having synthetic noise derived from Gaussian, Speckle and Poisson noise models. The experimental results show that the proposed method is efficient for noise elimination.

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Medical Image Denoising Using Adaptive Threshold Based on Contourlet Transform

Cited by 32 publications

References 10 publications

MRI Images Techniques

MRI Images Techniques

A Histogram based Hybrid Approach for Medical Image Denoising using Wavelet and Curvelet Transforms

An Approach based on Run Length Count for Denoising the Kannada Characters

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