Literature DB >> 1553390

Assessment of noise in a digital image using the join-count statistic and the Moran test.

K S Chuang1, H K Huang.   

Abstract

We assume that the data bits of a pixel in digital images can be divided into signal and noise bits. The signal bits occupy the most significant part of the pixel and the noise bits the least significant part. The signal part of each pixel are correlated while the noise parts are uncorrelated. Two statistical methods, the Moran test and the join-count statistic, are used to examine the noise parts. Images from three digital modalities--computerized tomography, magnetic resonance and computed radiography--are used for the evaluation of the noise bits. A residual image is formed by subtracting the original image from its smoothed version. The noise level in the residual image is then identical to that in the original image. Both statistical tests are then performed on the bit planes of the residual image. The results show that most digital images contain only 8-9 bits of correlated information. Both methods are easy to implement and fast to perform.

Mesh:

Year:  1992        PMID: 1553390     DOI: 10.1088/0031-9155/37/2/004

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  5 in total

1.  A blurring index for medical images.

Authors:  Tzong-Jer Chen; Keh-Shih Chuang; Jen-Hao Chang; Ya-Hui Shiao; Chun-Chao Chuang
Journal:  J Digit Imaging       Date:  2006-06       Impact factor: 4.056

2.  Quality of compressed medical images.

Authors:  Ya-Hui Shiao; Tzong-Jer Chen; Keh-Shih Chuang; Cheng-Hsun Lin; Chun-Chao Chuang
Journal:  J Digit Imaging       Date:  2007-02-22       Impact factor: 4.056

3.  Influence of image metrics when assessing image quality from a test object in cardiac X-ray systems: Part II.

Authors:  Roberto Sanchez; Eliseo Vano; Carlos Ubeda; Jose M Fernandez; Stephen Balter; Bart Hoornaert
Journal:  J Digit Imaging       Date:  2012-08       Impact factor: 4.056

4.  FISST based method for multi-target tracking in the image plane of optical sensors.

Authors:  Yang Xu; Hui Xu; Wei An; Dan Xu
Journal:  Sensors (Basel)       Date:  2012-03-02       Impact factor: 3.576

5.  Blind blur assessment of MRI images using parallel multiscale difference of Gaussian filters.

Authors:  Michael E Osadebey; Marius Pedersen; Douglas L Arnold; Katrina E Wendel-Mitoraj
Journal:  Biomed Eng Online       Date:  2018-06-13       Impact factor: 2.819

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.