Visual Perception and Quality Assessment

Moorthy, Anush K.; Wang, Zhou; Bovik, Alan C.

doi:10.1002/9783527635245.ch19

Cited by 14 publications

(8 citation statements)

References 72 publications

(94 reference statements)

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“…MSE shows the difference between the reconstructed vector image and the reference image. A low MSE value indicates two vectors are equal [27]. MSE is also referred to as noise power, a small value in MSE indicates that the noise in the image is small.…”

Section: Resultsmentioning

confidence: 99%

Planar Scintigraphy Image De-Noising Using Coiflet Wavelet

Puspitasari

Ningsih

Ridwan

et al. 2021

gnd

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The planar scintigraphic image usually has poor resolution and contains noise. This noise can be removed using the coiflet wavelet method so that the image quality gets better. This coiflet wavelet method is a noise reduction method based on frequency analysis. The planar scintigraphy image is the reconstructed image of the gamma radiation count data (phantom with the Cs-137 source in it). The original image is 15×15 pixel. Before the de-noising process, the image went through an interpolation process, which is to increase the pixel size of the image. The original image enlarged to 70×70, 480×480, and 1200×1200 pixel. After de-noising with coiflet wavelet, the image quality is measured based on MSE and PSNR parameters. The resulting images are quite good, with MSE values are close to zero and PSNR values of more than 60 dB. The smaller the MSE and the bigger the PSNR, is getting the better the image quality. In this study, the results show that the 1200×1200 pixel image has the best quality. It means that the image enlargement process has a good effect on the de-noising process, especially if the original image has a low resolution.

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Section: Resultsmentioning

confidence: 99%

Planar Scintigraphy Image De-Noising Using Coiflet Wavelet

Puspitasari

Ningsih

Ridwan

et al. 2021

gnd

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“…The values MSSIM exhibit greater consistency with the visual quality [17]. The Visual Information fidelity parameter (VIF) quantifies Shannon information that is shared between the reference and distorted images with respect to the information contained in the reference image itself [18]. VIF test is then evaluated as:…”

Section: The Encoding Algorithm Spiht (Set Partitioning In Hierarchicmentioning

confidence: 99%

Evaluation of the Medical Image Compression using Wavelet Packet Transform and SPIHT Coding

Benyahia¹,

Beladgham²,

Bassou³

2018

IJECE

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Wavelet transforms and wavelet packets are widely imposed in the analysis and resolution of problems related to science and technical engineering. Decomposition wavelet packet allows several frequency bands according to various levels of resolutions. We apply this transform (PWT) coupled with the SPIHT coder to reduce the limitations of conventional wavelet filter bank. The results obtained using the applied algorithm, are very satisfactory and encouraging compared to many of the best coders cited in the literature and show a visual and numerical superiority over conventional methods. These the promising results are confirmed by visual evaluation parameters (PSNR, MSSIM and VIF).

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“…It then computes E = C + N and F = D + N'. The VIF criterion is then evaluated as (Dumic et al, 2010;Moorthy et al, 2010;Wang and Li, 2011):…”

Section: The Visual Information Fidelitymentioning

confidence: 99%

Gray scale and colour medical image compressed using hybrid contourlet biorthogonal CDF lifting scheme, bandelet and quincunx wavelet transforms: a comparative study

Hacene

Bessaid

2018

IJBET

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The Quincunx wavelet, the lifting scheme wavelet and the second generation bandelet transform are a new method to offer an optimal representation for image geometric. In the field of medical diagnostics, interested parties have resorted increasingly to medical imaging. It is well established that the accuracy and completeness of diagnosis are initially connected with the image quality, but the quality of the image is itself dependent on a number of factors including primarily the processing that an image must undergo to enhance its quality. The quality evaluation of compressed image is necessary to judge the performance of a compression method. This paper introduces an algorithm for medical image compression based on hybrid non-subsampled contourlet (NSCT) and quincunx wavelet transforms (QWT) coupled with SPIHT coding algorithm, of which we present the objective measurements (PSNR, EDGE, WPSNR, MSSIM, VIF, and WSNR) in order to evaluate the quality of the image.

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Visual Perception and Quality Assessment

Cited by 14 publications

References 72 publications

Planar Scintigraphy Image De-Noising Using Coiflet Wavelet

Planar Scintigraphy Image De-Noising Using Coiflet Wavelet

Evaluation of the Medical Image Compression using Wavelet Packet Transform and SPIHT Coding

Gray scale and colour medical image compressed using hybrid contourlet biorthogonal CDF lifting scheme, bandelet and quincunx wavelet transforms: a comparative study

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