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Continuous wavelet transform-based no-reference quality assessment of deblocked images
by
Joshi, Piyush
, Rawat, Sonika
, Prakash, Surya
in
Algorithms
/ Artificial Intelligence
/ Computer Graphics
/ Computer Science
/ Continuous wavelet transform
/ Estimates
/ Fourier transforms
/ Image compression
/ Image degradation
/ Image Processing and Computer Vision
/ Image quality
/ Original Article
/ Probability
/ Quality assessment
/ Wavelet transforms
2018
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Continuous wavelet transform-based no-reference quality assessment of deblocked images
by
Joshi, Piyush
, Rawat, Sonika
, Prakash, Surya
in
Algorithms
/ Artificial Intelligence
/ Computer Graphics
/ Computer Science
/ Continuous wavelet transform
/ Estimates
/ Fourier transforms
/ Image compression
/ Image degradation
/ Image Processing and Computer Vision
/ Image quality
/ Original Article
/ Probability
/ Quality assessment
/ Wavelet transforms
2018
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Do you wish to request the book?
Continuous wavelet transform-based no-reference quality assessment of deblocked images
by
Joshi, Piyush
, Rawat, Sonika
, Prakash, Surya
in
Algorithms
/ Artificial Intelligence
/ Computer Graphics
/ Computer Science
/ Continuous wavelet transform
/ Estimates
/ Fourier transforms
/ Image compression
/ Image degradation
/ Image Processing and Computer Vision
/ Image quality
/ Original Article
/ Probability
/ Quality assessment
/ Wavelet transforms
2018
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Continuous wavelet transform-based no-reference quality assessment of deblocked images
Journal Article
Continuous wavelet transform-based no-reference quality assessment of deblocked images
2018
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Overview
An image when passed through a compression process either gains noise or loses some information, resulting in a degraded image. JPEG is considered to be one of the most commonly used compression standards whose resulting images are found to be subjected to blocking artifacts at low bit rates. There exist a few deblocking algorithms which have been proposed in the literature to reduce the blocking artifacts in compressed images. However, unfortunately these deblocking techniques introduce blur distortion in the images and hence the deblocked images may contain multiple distortions. Existing image quality metrics have limitations in evaluating the quality of deblocked images as they are not designed for multiply distorted images. To overcome this issue, we propose a no-reference quality assessment technique for deblocked images using continuous wavelet transform. We evaluate the proposed technique on DBID database which consists of general deblocked images. Experimental results show that the proposed quality assessment technique outperforms the existing image quality assessment techniques for deblocked images.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
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