scholarly journals Picture-wise just noticeable difference prediction model for JPEG image quality assessment

2022 ◽  
Vol 70 (1) ◽  
pp. 62-86
Author(s):  
Boban Bondžulić ◽  
Boban Pavlović ◽  
Nenad Stojanović ◽  
Vladimir Petrović

Introduction/purpose: The paper presents interesting research related to the performance analysis of the picture-wise just noticeable difference (JND) prediction model and its application in the quality assessment of images with JPEG compression. Methods: The performance analysis of the JND model was conducted in an indirect way by using the publicly available results of subject-rated image datasets with the separation of images into two classes (above and below the threshold of visible differences). In the performance analysis of the JND prediction model and image quality assessment, five image datasets were used, four of which come from the visible wavelength range, and one dataset is intended for remote sensing and surveillance with images from the infrared part of the electromagnetic spectrum. Results: The pap 86 er shows that using a picture-wise JND model, subjective image quality assessment scores can be estimated with better accuracy, leading to significant performance improvements of the traditional peak signal-to-noise ratio (PSNR). The gain achieved by introducing the picture-wise JND model in the objective assessment depends on the chosen dataset and the results of the initial simple to compute PSNR measure, and it was obtained on all five datasets. The mean linear correlation coefficient (for five datasets) between subjective and PSNR objective quality estimates increased from 74% (traditional PSNR) to 90% (picture-wise JND PSNR). Conclusion: Further improvement of the JND-based objective measure can be obtained by improving the picture-wise model of JND prediction.

2016 ◽  
Vol 9 (3) ◽  
pp. 297-301 ◽  
Author(s):  
Amir R Honarmand ◽  
Ali Shaibani ◽  
Tamila Pashaee ◽  
Furqan H Syed ◽  
Michael C Hurley ◽  
...  

ObjectiveDifferent technical and procedural methods have been introduced to develop low radiation dose protocols in neurointerventional examinations. We investigated the feasibility of minimizing radiation exposure dose by simply decreasing the detector dose during cerebral DSA and evaluated the comparative level of image quality using both subjective and objective methods.MethodsIn a prospective study of patients undergoing diagnostic cerebral DSA, randomly selected vertebral arteries (VA) and/or internal carotid arteries and their contralateral equivalent arteries were injected. Detector dose of 3.6 and 1.2 μGy/frame were selected to acquire standard dose (SD) and low dose (LD) images, respectively. Subjective image quality assessment was performed by two neurointerventionalists using a 5 point scale. For objective image quality evaluation, circle of Willis vessels were categorized into conducting, primary, secondary, and side branch vessels. Two blinded observers performed arterial diameter measurements in each category. Only image series obtained from VA injections opacifying the identical posterior intracranial circulation were utilized for objective assessment.ResultsNo significant difference between SD and LD images was observed in subjective and objective image quality assessment in 22 image series obtained from 10 patients. Mean reference air kerma and kerma area product were significantly reduced by 61.28% and 61.24% in the LD protocol, respectively.ConclusionsOur study highlights the necessity for reconsidering radiation dose protocols in neurointerventional procedures, especially at the level of baseline factory settings.


Author(s):  
Agung W. Setiawan ◽  
Andriyan B. Suksmono ◽  
Tati R. Mengko ◽  
Oerip S. Santoso

The RGB color retinal image has an interesting characteristic, i.e. the G channel contains more important information than the other ones. One of the most important features in a retinal image is the retinal blood vessel structure. Many diseases can be diagnosed based on in the retinal blood vessel, such as micro aneurysms that can lead to blindness. In the G channel, the contrast between retinal blood vessel and its background is significantly high. The authors explore this retinal image characteristic to construct a more suitable image coding system. The coding processes are conduct in three schemes: weighted R channel, weighted G channel, and weighted B channel coding. Their hypothesis is that allocating more bits in the G channel will improve the coding performance. The authors seek for image quality assessment (IQA) metrics that can be used to measure the distortion in retinal image coding. Three different metrics, namely Peak Signal to Noise Ratio (PSNR), Structure Similarity (SSIM), and Visual Information Fidelity (VIF) are compared as objective assessment in image coding and to show quantitatively that G channel has more important role compared to the other ones. The authors use Vector Quantization (VQ) as image coding method due to its simplicity and low-complexity than the other methods. Experiments with actual retinal image shows that the minimum value of SSIM and VIF required in this coding scheme is 0.9940 and 0.8637.


2017 ◽  
Vol 63 (1) ◽  
pp. 99-107 ◽  
Author(s):  
Jayesh Ruikar ◽  
Ashoke Sinha ◽  
Saurabh Chaudhury

Abstract In literature, oriented filters are used for low-level vision tasks. In this paper, we propose use of steerable Gaussian filter in image quality assessment. Human visual system is more sensitive to multidirectional edges present in natural images. The most degradation in image quality is caused due to its edges. In this work, an edge based metric termed as steerable Gaussian filtering (SGF) quality index is proposed as objective measure for image quality assessment. The performance of the proposed technique is evaluated over multiple databases. The experimental result shows that proposed method is more reliable and outperform the conventional image quality assessment method.


Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2256
Author(s):  
Krzysztof Okarma ◽  
Piotr Lech ◽  
Vladimir V. Lukin

In the recent years, many objective image quality assessment methods have been proposed by different researchers, leading to a significant increase in their correlation with subjective quality evaluations. Although many recently proposed image quality assessment methods, particularly full-reference metrics, are in some cases highly correlated with the perception of individual distortions, there is still a need for their verification and adjustment for the case when images are affected by multiple distortions. Since one of the possible approaches is the application of combined metrics, their analysis and optimization are discussed in this paper. Two approaches to metrics’ combination have been analyzed that are based on the weighted product and the proposed weighted sum with additional exponential weights. The validation of the proposed approach, carried out using four currently available image datasets, containing multiply distorted images together with the gathered subjective quality scores, indicates a meaningful increase of correlations of the optimized combined metrics with subjective opinions for all datasets.


2019 ◽  
Vol 58 (2) ◽  
pp. 340
Author(s):  
Zijin Gu ◽  
Yong Ding ◽  
Ruizhe Deng ◽  
Xiaodong Chen ◽  
Andrey S. Krylov

2011 ◽  
Vol 474-476 ◽  
pp. 143-150
Author(s):  
Chun E Zhang ◽  
Fan Ci Guo ◽  
Ke Xiong

Image quality assessment plays an important role in various image processing applications. One of the challenges to objectively assess image quality is how to design an effective scheme to achieve high consistency with the classic subjective image assessment criterion, Mean Opinion Score (MOS). This work presents a novel objective assessment algorithm for binary images by considering three factors which have great influences on visual quality of binary images, i.e., structural change caused by noise point, isolated noise points, and gathering noise points. Experimental results show that our algorithm can achieve effective objective assessment results with higher consistency with the MOS criterion.


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