A Novel Image Quality Index for Image Quality Assessment

Islam, Sheikh Md. Rabiul; Huang, Xu; Le, Kim

doi:10.1007/978-3-642-42051-1_68

Cited by 10 publications

(4 citation statements)

References 5 publications

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“…The images are for 8-bit 256 × 256 pixels and 8-bit 64 × 64 pixels. We used different image quality indexes: PNSR, UIQI, Q(Skewness), Q(Kurtosis), SSIM, SSIM(Skewness), SSIM(Abs-Skewness), SSIM(Kurtosis) [19] [20] to evaluate the qualities of the compressed images. In order to make clearer comparisons, besides our proposed sparse basis CDF9/7 WT with three different measurements matrix's and Basis Pursuit (BP) algorithms or greedy optimization techniques as OMP and are also used.…”

Section: Resultsmentioning

confidence: 99%

“…To evaluate the compressed image using proposed quality indexes [19] [20] and others evaluation of image quality (EIQ) indexes.…”

Section: Stage 5: Evaluationmentioning

confidence: 99%

“…For comparison purposed of this novel work, we have also used sparse basis DWT and DCT of this paper. Experimental results on open sources database [18] show that our proposed approach with sparse basis on CDF9/7 wavelet transform in CS have higher qualities compressed image than traditional approach with sparse DWT and DCT in terms an image quality assessment scheme [19] [20]. This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Image Compression Based on Compressive Sensing Using Wavelet Lifting Scheme

Islam¹,

Huang²,

Ou³

2015

IJMA

Self Cite

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Many algorithms have been developed to find sparse representation over redundant dictionaries or transform. This paper presents a novel method on compressive sensing (CS)-based image compression using sparse basis on CDF9/7 wavelet transform. The measurement matrix is applied to the three levels of wavelet transform coefficients of the input image for compressive sampling. We have used three different measurement matrix as Gaussian matrix, Bernoulli measurement matrix and random orthogonal matrix. The orthogonal matching pursuit (OMP) and Basis Pursuit (BP) are applied to reconstruct each level of wavelet transform separately. Experimental results demonstrate that the proposed method given better quality of compressed image than existing methods in terms of proposed image quality evaluation indexes and other objective (PSNR/UIQI/SSIM) measurements.

show abstract

Section: Resultsmentioning

confidence: 99%

“…To evaluate the compressed image using proposed quality indexes [19] [20] and others evaluation of image quality (EIQ) indexes.…”

Section: Stage 5: Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Image Compression Based on Compressive Sensing Using Wavelet Lifting Scheme

Islam¹,

Huang²,

Ou³

2015

IJMA

Self Cite

View full text Add to dashboard Cite

show abstract

“…Besides, there is no specified means to evaluate the point spread function (PSF) of an X-ray imager, where removal of side lobes plays an important role. On the other hand, methods for evaluating image quality in various aspects, referred to as the image quality assessment (IQA) methods, have been developed and widely investigated in the computing and engineering field, especially over the last two decades (e.g., Wang and Li, 2011;Islam, Huang, and Le, 2013). As introduced in Sara, Akter, and Uddin (2019), the objective image quality merits are classified mainly into two groups: full-reference (FR) measurements and no-reference (NR) measurements.…”

Section: Introductionmentioning

confidence: 99%

A New Index for Assessing Quality of Solar X-ray Imaging System and Image Reconstruction

Li,

Yu,

et al. 2024

Preprint

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Indirect X-ray modulation imaging has been adopted in a number of solar missions and provided reconstructed X-ray images of solar flares that are of great scientific importance. However, the assessment of the image quality of the reconstruction is still difficult which is particularly useful for scheme design of X-ray imaging systems, improvement and testing of imaging algorithms, and scientific research. Currently, there is no specified method to quantitatively evaluate the quality of X-ray images. In this paper, we first propose percentage proximity degree (PPD) by considering the imaging characteristics of X-ray sources and in particular, side lobes and their effects on imaging quality. After screening a variety of imaging quality assessments through systematic testing of six aspects, we utilized the technique for order preference by similarity to ideal solution to the indices that meet the requirements. The final quality index established for X-ray image reconstruction (QuIX), consists of the selected indices and the new PPD, performs well on all the aspects, including assessment of PSF (point spread function) of ASO-S/HXI and simulation tests under different grid configurations, and imaging tests with RHESSI data. It was also found to be a useful tool in determination of proper imaging algorithm and field of view (FOV) for image reconstruction.

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A Novel Adaptive Shrinkage Threshold on Shearlet Transform for Image Denoising

Islam

Huang

2014

Neural Information Processing

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A Novel Image Quality Index for Image Quality Assessment

Cited by 10 publications

References 5 publications

Image Compression Based on Compressive Sensing Using Wavelet Lifting Scheme

Image Compression Based on Compressive Sensing Using Wavelet Lifting Scheme

A New Index for Assessing Quality of Solar X-ray Imaging System and Image Reconstruction

A Novel Adaptive Shrinkage Threshold on Shearlet Transform for Image Denoising

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