Subjective Score Predictor: A New Evaluation Function of Distorted Image Quality

Image quality assessment (IQA) is a method to evaluate the perceptual performance of image. Many objective IQA algorithms are developed from the objective comparison of image features, which are mainly trained and evaluated from the ground truth of subjective scores. Due to the inconsistent experiment conditions and cumbersome observing processes of subjective experiments, it is imperative to generate the ground truth for IQA research via objective computation methods. In this paper, we propose a subjective score predictor (SSP) aiming to provide the ground truth of IQA datasets. In perfect accord with distortion information, the distortion strength of distorted image is employed as a dependent parameter. To further be consistent with subjective opinion, on the one hand, the subjective score of source image is viewed as a quality base value, and, on the other hand, we integrate the distortion parameter and the quality base value into a human visual model function to obtain the final SSP value. Experimental results demonstrate the advantages of the proposed SSP in the following aspects: effective performance to reflect the distortion strength, competitive ground truth, and valid evaluation for objective IQA methods as well as subjective scores

Active sampling, scaling and dataset merging for large-scale image quality assessment

The field of subjective assessment is concerned with eliciting human judgements about a set of stimuli. Collecting such data is costly and time-consuming, especially when the subjective study is to be conducted in a controlled environment and using a specialized equipment. Thus, data from these studies are usually scarce. One of the areas, for which obtaining subjective measurements is difficult is image quality assessment. The results from these studies are used to develop and train automated or objective image quality metrics, which, with the advent of deep learning, require large amounts of versatile and heterogeneous data. I present three main contributions in this dissertation. First, I propose a new active sampling method for efficient collection of pairwise comparisons in subjective assessment experiments. In these experiments observers are asked to express a preference between two conditions. However, many pairwise comparison protocols require a large number of comparisons to infer accurate scores, which may be unfeasible when each comparison is time-consuming (e.g. videos) or expensive (e.g. medical imaging). This motivates the use of an active sampling algorithm that chooses only the most informative pairs for comparison. I demonstrate, with real and synthetic data, that my algorithm offers the highest accuracy of inferred scores given a fixed number of measurements compared to the existing methods. Second, I propose a probabilistic framework to fuse the outcomes of different psychophysical experimental protocols, namely rating and pairwise comparisons experiments. Such a method can be used for merging existing datasets of subjective nature and for experiments in which both measurements are collected. Third, with a new dataset merging technique and by collecting additional cross-dataset quality comparisons I create a Unified Photometric Image Quality (UPIQ) dataset with over 4,000 images by realigning and merging existing high-dynamic-range (HDR) and standard-dynamic-range (SDR) datasets. The realigned quality scores share the same unified quality scale across all datasets. I then use the new dataset to retrain existing HDR metrics and show that the dataset is sufficiently large for training deep architectures. I show the utility of the dataset and metrics in an application to image compression that accounts for viewing conditions, including screen brightness and the viewing distance

Quality Assessment for CRT and LCD Color Reproduction Using a Blind Metric

This paper deals with image quality assessment that is capturing the focus of several research teams from academic and industrial parts. This field has an important role in various applications related to image from acquisition to projection. A large numbers of objective image quality metrics have been developed during the last decade. These metrics are more or less correlated to end-user feedback and can be separated in three categories: 1) Full Reference (FR) trying to evaluate the impairment in comparison to the reference image, 2) Reduced Reference (RR) using some features extracted from an image to represent it and compare it with the distorted one and 3) No Reference (NR) measures known as distortions such as blockiness, blurriness,. . .without the use of a reference. Unfortunately, the quality assessment community have not achieved a universal image quality model and only empiricalmodels established on psychophysical experimentation are generally used. In this paper, we focus only on the third category to evaluate the quality of CRT (Cathode Ray Tube) and LCD (Liquid Crystal Display) color reproduction where a blind metric is, based on modeling a part of the human visual system behavior. The objective results are validated by single-media and cross-media subjective tests. This allows to study the ability of simulating displays on a reference one

Assessment of speckle denoising filters for digital holography using subjective and objective evaluation models

Digital holography is an emerging imaging technique for displaying and sensing three dimensional objects. The perceived image quality of a hologram is frequently corrupted by speckle noise due to coherent illumination. Although several speckle noise reduction methods have been developed so far, there are scarce quality assessment studies to address their performance and they typically focus solely on objective metrics. However, these metrics do not reflect the visual quality perceived by a human observer. In this work, the performance of four speckle reduction algorithms, namely the nonlocal means, the Lee, the Frost and the block matching 3D filters, with varying parameterizations, were subjectively evaluated. The results were ranked with respect to the perceived image quality to obtain the mean opinion scores using pairwise comparison. The correlation between the subjective results and twenty different no-reference objective quality metrics was evaluated. The experiment indicates that block matching 3D and Lee are the preferred filters, depending on hologram characteristics. The best performing objective metrics were identified for each filter.info:eu-repo/semantics/publishedVersio

Comparison of Image Quality Measuring Methods

Táto práca sa zaoberá metódami merajúcimi kvalitu obrazu a porovnaním ich výkonnosti v súvislosti s kompresnými štandardmi JPEG a JPEG 2000. V prvej časti približuje problematiku merania kvality obrazu, zmieňuje existujúce a používané metódy a detailnejšie popisuje vybrané z nich. V druhej časti popisuje použitý postup pri získaní subjektívneho a objektívneho hodnotenia kvality obrázkov. Ďalej porovnáva získané subjektívne výsledky a výsledky určené objektívnymi metódami. Záver poskytuje vyhodnotenie získaných výsledkov a určenie najvhodnejších metód na meranie kvality obrázkov vytvorených pomocou vyššie uvedených kompresných štandardov.This thesis is aimed at image quality assessment methods and comparison of their performance regarding compression standards JPEG and JPEG 2000. First part provides information about image quality assessment basics, mentioning existing and used methods. The second part describes approach used to acquire subjective and objective rating of image quality. Further it compares obtained subjective ratings and ratings determined by objective methods. Conclusion provides an evaluation of obtained results and specification of the most suitable methods for measuring quality of images created by compression standards stated above.

A comparison of alternative approaches to MR cardiac triggering: A pilot study at 3 Tesla

This pilot comparative study evaluates the usability of the alternative approaches to magnetic resonance (MR) cardiac triggering based on ballistocardiography (BCG): fiber-optic sensor (O-BCG) and pneumatic sensor (P-BCG). The comparison includes both the objective and subjective assessment of the proposed sensors in comparison with a gold standard of ECG-based triggering. The objective evaluation included several image quality assessment (IQA) parameters, whereas the subjective analysis was performed by 10 experts rating the diagnostic quality (scale 1 - 3, 1 corresponding to the best image quality and 3 the worst one). Moreover, for each examination, we provided the examination time and comfort rating (scale 1 - 3). The study was performed on 10 healthy subjects. All data were acquired on a 3 T SIEMENS MAGNETOM Prisma. In image quality analysis, all approaches reached comparable results, with ECG slightly outperforming the BCG-based methods, especially according to the objective metrics. The subjective evaluation proved the best quality of ECG (average score of 1.68) and higher performance of P-BCG (1.97) than O-BCG (2.03). In terms of the comfort rating and total examination time, the ECG method achieved the worst results, i.e. the highest score and the longest examination time: 2.6 and 10:49 s, respectively. The BCG-based alternatives achieved comparable results (P-BCG 1.5 and 8:06 s; OBCG 1.9, 9:08 s). This study confirmed that the proposed BCG-based alternative approaches to MR cardiac triggering offer comparable quality of resulting images with the benefits of reduced examination time and increased patient comfort.Web of Science2662605259

Psychometric scaling of TID2013 dataset

TID2013 is a subjective image quality assessment dataset with a wide range of distortion types and over 3000 images. The dataset has proven to be a challenging test for objective quality metrics. The dataset mean opinion scores were obtained by collecting pairwise comparison judgments using the Swiss tournament system, and averaging votes of observers. However, this approach differs from the usual analysis of multiple pairwise comparisons, which involves psychometric scaling of the comparison data using either Thurstone or Bradley-Terry mod- els. In this paper we investigate how quality scores change when they are computed using such psychometric scaling instead of averaging vote counts. In order to properly scale TID2013 quality scores, we conduct four additional experiments of two different types, which we found necessary to produce a common quality scale: comparisons with reference images, and cross-content comparisons. We demonstrate on a fifth validation experiment that the two additional types of comparisons are necessary and in conjunction with psychometric scaling improve the consistency of quality scores, especially across images depicting different contents