IHNS: A Pragmatic Investigation on Identifying Highly Noisy Subband in FMDFB for Fixing Threshold to Deteriorate Noise in Images

Sutha, S.; Leavline, E. Jebamalar; Singh, Danasingh Asir Antony Gnana

doi:10.3923/itj.2013.1289.1298

Search citation statements

Order By: Relevance

Paper Sections

Select...

Mathematical Modeling Of Fmdfb Coefficients1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2014

2016

Publication Types

Select...

Article2

Relationship

Self Cite1

Independent1

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A computationally efficient and accurate model of FMDFB coefficients is necessary to assist straightforward parameter estimation needed for various image processing applications (Sutha, Leavline, & Gnana Singh, 2013). First, to find a suitable statistical model (Kwitt, 2010), the frequency distribution of FMDFB subbands need to be analyzed.…”

Section: Mathematical Modeling Of Fmdfb Coefficientsmentioning

confidence: 99%

Analysis and Modeling of Statistical Properties of FMDFB Subband Coefficients

Leavline

Sutha²

2016

J. Mod. App. Stat. Meth.

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Mathematical Modeling Of Fmdfb Coefficientsmentioning

confidence: 99%

Analysis and Modeling of Statistical Properties of FMDFB Subband Coefficients

Leavline

Sutha²

2016

J. Mod. App. Stat. Meth.

Self Cite

View full text Add to dashboard Cite

show abstract

Fast multiscale directional filter bank-based speckle mitigation in gallstone ultrasound images

Leavline

Sutha²,

Singh

2014

J. Opt. Soc. Am. A

View full text Add to dashboard Cite

Speckle noise is a multiplicative type of noise commonly seen in medical and remote sensing images. It gives a granular appearance that degrades the quality of the recorded images. These speckle noise components need to be mitigated before the image is used for further processing and analysis. This paper presents a novel approach for removing granular speckle noise in gray scale images. We used an efficient multiscale image representation scheme named fast multiscale directional filter bank (FMDFB) along with simple threshold methods such as Vishushrink for image processing. It is a perfect reconstruction framework that can be used for a wide range of image processing applications because of its directionality and reduced computational complexity. The FMDFB-based speckle mitigation is appealing over other traditional multiscale approaches such as wavelets and Contourlets. Our experimental results show that the despeckling performance of the proposed method outperforms the wavelet and Contourlet-based despeckling methods.

show abstract

IHNS: A Pragmatic Investigation on Identifying Highly Noisy Subband in FMDFB for Fixing Threshold to Deteriorate Noise in Images

Cited by 2 publications

References 12 publications

Analysis and Modeling of Statistical Properties of FMDFB Subband Coefficients

Analysis and Modeling of Statistical Properties of FMDFB Subband Coefficients

Fast multiscale directional filter bank-based speckle mitigation in gallstone ultrasound images

Contact Info

Product

Resources

About