Subjective Quality Evaluation Research Articles

(Retracted) Infrared image filtering and enhancement processing method based upon image processing technology

Due to the processing method used in many existing image enhancement algorithms, some inherent noise in the image is amplified when the image is enhanced globally or locally. The quality of infrared images directly affects the wide application of infrared imaging technology, yet the quality of infrared image depends largely on the advanced nature and correct application of infrared image processing technology (IPT). This research mainly discusses the infrared image filtering enhancement processing method based on IPT. We briefly summarize the research significance, application fields and research status of the image registration and enhancement. We summarize the commonly used methods. We use a contrast saliency filter to obtain the region of interest and perform statistical segmentation on the region to make it more suitable for observation and subsequent processing. No matter what the background environment is, the image detail enhancement algorithm enhances all the details in the image in a balanced manner. Therefore, we adopt the scheme of separating the background and the details to avoid the influence of the background difference on the detail display effect in other enhancement methods. Objective experiments have also proved that it is difficult to achieve consistency between subjective and objective evaluation of image quality. Therefore, the evaluation of processed image quality still needs to combine subjective visual effects and objective evaluation. We use optimized hierarchical differential expression theory to solve the acquired saliency region and obtain the differential vector that realizes the gray difference amplification of this region. The dynamic range of the original image is very narrow, roughly concentrated in [0, 50]. The gray range of the image processed by the enhancement algorithm has been well expanded, basically covering [0, 255]. The proposed infrared image enhancement method achieves a better visual enhancement effect.

Первые результаты применения стволовых клеток в лечении стрессового недержания мочи у женщин

Introduction. Stress urinary incontinence is a problem not only for the female, but is also a social, medical and economic issue for the community. The main method of treating stress urinary incontinence in women is surgical intervention with the use of synthetic mesh tape. Possibilities of intra and post-surgical complications is a major setback of surgical treatment. Attempts to restore/improve urethral sphincter functions by implanting stem cells has become a perspective method. Methods and materials. Ten female patients from the Urological Clinic of the Grodno State Medical University were chosen for treatment using autologous mesenchymal stem cells. All of them were undergone tourological and gynecological examinations. All chosen patients filled in an Incontinence Quality of Life questionnaire, related to the continention of urine before and after the implant of stem cells. After the explantation of fatty tissue, autologous mesenchymal stem cells were extracted and cultivated, a mixture of stem cells with a gelatine-based substance. Stem cells were introduced para-urethrally and into the urethral wall. Results. After 12 months after the implant 9 women completely retained urine during physical activity. No imperative disorders noted. One patient continued losing urine during physical activity, and her condition remained without improvement. Conclusion. A positive result by criteria of urine retention, urination disorder, and a subjective evaluation of quality of life was achieved in 90% of patients. A lack of even a small positive effect on one patient gives evidence to pathological changes in the organs of the genitourinary, in which stem cell therapy has a low effectiveness. First results inspire a careful optimism, but a continuation of research is required due to a small number of observations.

The regulatory adaptive status in hypertensive patients with congestive heart failure with preserved left ventricular ejection fraction: the effects of fosinopril versus zofenopril

Objective. To evaluate the impact of fosinopril versus zofenopril on the regulatory adaptive status (RAS) in hypertensive patients with chronic heart failure (CHF) with preserved left ventricular (LV) ejection fraction (EF). Design and methods. The study inclded 67 hospitalized patients with hypertension (HTN) and CHF I–II NYHA functional classes with LV EF ≥ 50 %, who were randomized into two groups for treatment with fosinopril (13,8 ± 4,1 mg/day, n = 32) or zofenopril (17,9 ± 5,9 mg/day, n = 35). All patients additionally received nebivolol (7,1 ± 1,9 and 6,9 ± 1,8 mg/day), and if needed, atorvastatin and acetylsalicylic acid were prescribed. At baseline and after 24 weeks, we performed quantitative assessment of RAS-regulatory-adaptive capabilities (by cardio-respiratory coupling test), echocardiography, treadmill test, six-minute walking test, assessment of the N-terminal brain natriuretic pro-peptide level in blood plasma, subjective evaluation of quality of life (QL). Results. Fosinopril versus zofenopril led to a greater improvement of RAS (by 69,0%, p < 0,01 versus 41,1%, p < 0,01) and to a higher increase in tolerance to physical activity: longer distance in a six-minute walk test (by 28,1 %, p < 0,05 versus 25,9 %, p < 0,05), improvement in functional class of CHF (from II to I in 56 % of patients, in 25 % CHF was not registered versus change from II to I in 42 % of patients, and no CHF in 14 %). In both groups, cardiac diastolic function improved (decreased VE/Ve by 39,5%, p < 0,01 and 37,8%, p < 0,01), neurohumoral hyperactivity reduced (NT-proBNP decreased by 40,6 %, p < 0,01 and 39,4 %, p < 0,01), and subjective QL increased (decrease in the amount of negative points by 69,3%, p < 0,01, and 64,9 %, p < 0,01). Conclusions . In HTN patients with CHF with preserved LV EF, fosinopril versus zofenopril may be preferable due to a greater impact on regulatory and adaptive capabilities.

Subjective and Objective Quality Evaluation for Underwater Image Enhancement and Restoration

Since underwater imaging is affected by the complex water environment, it often leads to severe distortion of the underwater image. To improve the quality of underwater images, underwater image enhancement and restoration methods have been proposed. However, many underwater image enhancement and restoration methods produce over-enhancement or under-enhancement, which affects their application. To better design underwater image enhancement and restoration methods, it is necessary to research the underwater image quality evaluation (UIQE) for underwater image enhancement and restoration methods. Therefore, a subjective evaluation dataset for an underwater image enhancement and restoration method is constructed, and on this basis, an objective quality evaluation method of underwater images, based on the relative symmetry of underwater dark channel prior (UDCP) and the underwater bright channel prior (UBCP) is proposed. Specifically, considering underwater image enhancement in different scenarios, a UIQE dataset is constructed, which contains 405 underwater images, generated from 45 different underwater real images, using 9 representative underwater image enhancement methods. Then, a subjective quality evaluation of the UIQE database is studied. To quantitatively measure the quality of the enhanced and restored underwater images with different characteristics, an objective UIQE index (UIQEI) is used, by extracting and fusing four groups of features, including: (1) the joint statistics of normalized gradient magnitude (GM) and Laplacian of Gaussian (LOG) features, based on the underwater dark channel map; (2) the joint statistics of normalized gradient magnitude (GM) and Laplacian of Gaussian (LOG) features, based on the underwater bright channel map; (3) the saturation and colorfulness features; (4) the fog density feature; (5) the global contrast feature; these features capture key aspects of underwater images. Finally, the experimental results are analyzed, qualitatively and quantitatively, to illustrate the effectiveness of the proposed UIQEI method.

Perceptual Quality Assessment of HEVC and VVC Standards for 8K Video

With the growing data consumption of emerging video applications and users’ requirement for higher resolutions, up to 8K, a huge effort has been made in video compression technologies. Recently, versatile video coding (VVC) has been standardized by the moving picture expert group (MPEG), providing a significant improvement in compression performance over its predecessor high efficiency video coding (HEVC). In this paper, we provide a comparative subjective quality evaluation between VVC and HEVC standards for 8K resolution videos. In addition, we evaluate the perceived quality improvement offered by 8K over UHD 4K resolution. The compression performance of both VVC and HEVC standards has been conducted in random access (RA) coding configuration, using their respective reference software, VVC test model (VTM-11) and HEVC test model (HM-16.20). Objective measurements, using PSNR, MS-SSIM and VMAF metrics have shown that the bitrate gains offered by VVC over HEVC for 8K video content are around 31%, 26% and 35%, respectively. Subjectively, VVC offers an average of around 41% of bitrate reduction over HEVC for the same visual quality. A compression gain of 50% has been reached for some tested video sequences regarding a Student’s t-test analysis. In addition, for most tested scenes, a significant visual difference between uncompressed 4K and 8K has been noticed.

Quality analysis of point cloud coding solutions

In this paper, a subjective quality based comparison between four point clouds codecs is presented. For that, a set of six point clouds was chosen. They were coded with four different point cloud encoding solutions, notably the MPEG V-PCC and G-PCC, a deep learning coding solution RS-DLPCC and also Draco, with different bit rates. A subjective test where the distorted and reference point clouds were rotated in a video sequence side by side followed by the quality evaluation, was conducted. Then the performance of a set of four point cloud objective quality metrics of he quality, was analysed using the subjective quality evaluation results. These metrics are usually reported as providing a good representation and are often used to evaluate compression solutions. In fact, the studied metrics tend to provide a good representation for V-PCC and G-PCC, an acceptable representation for RS-DLPCC, and a bad representation for Draco. It was also concluded that V-PCC is the best codec of the studied ones. The deep learning based solution still performs worst than the two MPEG codecs.

Tensor Product and Tensor-Singular Value Decomposition Based Multi-Exposure Fusion of Images

Considering multidimensional structure of the multi-exposure images, a new Tensor product and Tensor-singular value decomposition based Multi-Exposure image Fusion (TT-MEF) method is proposed. The main innovation of this work is to explore a new feature representation of multi-exposure images in the new tensor domain and design the fusion strategy on this basis. Specifically, the luminance and the chrominance channels are fused separately to maintain color consistency. For the luminance fusion, the luminance channel of multi-exposure images is divided into two parts, that is, de-mean term and mean term. The de-mean term is represented as a tensor to extract the feature. Then, the tensor product and tensor-singular value decomposition (T-SVD) are used to design a tensor feature extractor. Furthermore, a fusion strategy of the de-mean term is presented according to the visual saliency model, and a fusion strategy of the mean term is defined by the local and the global visual weights to control counterpoise between the local and global luminance. For the chrominance fusion, a new fusion strategy is also designed by the tensor product and T-SVD, similar to the luminance fusion. Finally, the fused image is obtained by combining the luminance and chrominance fusion. Experimental results show that the proposed TT-MEF method generally outperforms the existing state-of-the-art in terms of subjective visual quality and objective evaluation.

Low Quality and Recognition of Image Content

Assessment of visual encryption of video and image content requires a reliable estimation of content recognizability and low quality. As pointed out in the literature, current methods are insufficient and research into this topic, as well as into the relation between low quality and recognizability, is still lacking. This lack of research is primarily due to a lack of data. To improve on the status-quo we have taken a recognizability database and performed a subjective quality evaluation on a subset of the images. This gives us a new database with both subjective recognizability and quality information and allows to delve into the relation between low quality and recognizability. We analyze the relationship between quality and recognizability as well as the predictive quality of state of the art visual quality indices. We show that the visual quality indices are poor indicators for the estimation of recognizability. Furthermore, we show that they must be a poor fit because of the disparity between two distinct perceptual tasks: quality and recognizability.

Evaluation of Objective Distortion Measures for Automatic Quality Assessment of Processed PPG Signals for Real-Time Health Monitoring Devices

Real-time photoplethysmogram (PPG) denoising and data compression has become most essential requirements for accurately measuring vital parameters and efficient data transmission but that may introduce different kinds of waveform distortions due to the lossy processing techniques. Subjective quality assessment tests are the most reliable way to assess the quality, but they are time expensive and also cannot be incorporated with quality-driven compression mechanism. Thus, finding a best objective distortion measure is highly demanded for automatically evaluating quality of reconstructed PPG signal that must be subjectively meaningful and simple. In this paper, we present four types of objective distortion measures and evaluate their performance in terms of quality prediction accuracy, Pearson correlation coefficient and computational time. The performance evaluation is performed on different kinds of PPG waveform distortions introduced by the predictive coding, compressed sampling, discrete cosine transform and discrete wavelet transform. On the normal and abnormal PPG signals taken from five standard databases, evaluation results showed that different subjective quality evaluation groups (5-point, 3-point and 2-point rating scale) had different best objective distortion measures in terms of prediction accuracy and Pearson correlation coefficient. Moreover, selection of a best objective distortion measure depends upon type of PPG features that need to be preserved in the reconstructed signal.

Method for studying the dependence of the visibility of artifacts in an image on its physical dimensions

An actual size of screen proposed displays video sequence influence the process of creating subjective quality evaluation of multimedia content perception on various devices. The question of display size and resolution impact on improvements in perceived visual quality still remains unclear. Any decisions on display size must demand understanding of physical, perceptual and cognitive opportunities of each user, also physical working/operational environment constrains. In proposed paper presented a method allowing to dynamically change the visual quality of a typical media content depending on the physical size of the display. The unique contribution of proposed study for the first time represents method ology of the degraded video images association with streaming video and their effects on various display sizes with fixed screen parameters. Method can be used for scientific purposes related to practical applications for visualization technologies, signal reception and processing in information technology devices, also in related areas such as marketing, advertising, film industry.

Confusing Image Quality Assessment: Toward Better Augmented Reality Experience.

With the development of multimedia technology, Augmented Reality (AR) has become a promising next-generation mobile platform. The primary value of AR is to promote the fusion of digital contents and real-world environments, however, studies on how this fusion will influence the Quality of Experience (QoE) of these two components are lacking. To achieve better QoE of AR, whose two layers are influenced by each other, it is important to evaluate its perceptual quality first. In this paper, we consider AR technology as the superimposition of virtual scenes and real scenes, and introduce visual confusion as its basic theory. A more general problem is first proposed, which is evaluating the perceptual quality of superimposed images, i.e., confusing image quality assessment. A ConFusing Image Quality Assessment (CFIQA) database is established, which includes 600 reference images and 300 distorted images generated by mixing reference images in pairs. Then a subjective quality perception experiment is conducted towards attaining a better understanding of how humans perceive the confusing images. Based on the CFIQA database, several benchmark models and a specifically designed CFIQA model are proposed for solving this problem. Experimental results show that the proposed CFIQA model achieves state-of-the-art performance compared to other benchmark models. Moreover, an extended ARIQA study is further conducted based on the CFIQA study. We establish an ARIQA database to better simulate the real AR application scenarios, which contains 20 AR reference images, 20 background (BG) reference images, and 560 distorted images generated from AR and BG references, as well as the correspondingly collected subjective quality ratings. Three types of full-reference (FR) IQA benchmark variants are designed to study whether we should consider the visual confusion when designing corresponding IQA algorithms. An ARIQA metric is finally proposed for better evaluating the perceptual quality of AR images. Experimental results demonstrate the good generalization ability of the CFIQA model and the state-of-the-art performance of the ARIQA model. The databases, benchmark models, and proposed metrics are available at: https://github.com/DuanHuiyu/ARIQA.

Understanding the perceived quality of video predictions

The study of video prediction models is believed to be a fundamental approach to representation learning for videos. While a plethora of generative models for predicting the future frame pixel values given the past few frames exist, the quantitative evaluation of the predicted frames has been found to be extremely challenging. In this context, we study the problem of quality assessment of predicted videos. We create the Indian Institute of Science Predicted Videos Quality Assessment (IISc PVQA) Database consisting of 300 videos, obtained by applying different prediction models on different datasets, and accompanying human opinion scores. We collected subjective ratings of quality from 50 human participants for these videos. Our subjective study reveals that human observers were highly consistent in their judgments of quality of predicted videos. We benchmark several popularly used measures for evaluating video prediction and show that they do not adequately correlate with these subjective scores. We introduce two new features to effectively capture the quality of predicted videos, motion-compensated cosine similarities of deep features of predicted frames with past frames, and deep features extracted from rescaled frame differences. We show that our feature design leads to state-of-the-art quality prediction in accordance with human judgments on our IISc PVQA Database. The database and code are publicly available on our project website: https://nagabhushansn95.github.io/publications/2020/pvqa.

Analysis of Correlation between Quality of Life and Subjective Evaluation of Air Quality—Empirical Research Based on CHARLS 2018 Data

This paper mainly focuses on the relationship between the subjective evaluation of air quality and the quality of life (QOL) of middle-aged and elderly residents in China. The 2018 China Health and Retirement Longitudinal Study (CHARLS) project database is the key sources of data, from which 16,736 valid samples were used in our research. Multivariate linear regression analysis and binomial logistic regression model were applied to detect the impact of the subjective evaluation of air quality on QOL, which was evaluated in two dimensions, which are health utility and experienced utility, using the health utility EQ-5D score and the experienced utility of life satisfaction score. Our results show that there is a significant positive correlation between the subjective evaluation of air quality and the two dimensions of QOL. Age, education, marital status and sleep status also have a relatively great impact on the QOL of residents. This worked studied the overall QOL of middle-aged and elderly residents in China, while policy suggestions regarding high-quality air public goods are also given in the paper.

Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover

The process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus) system is one of the leading standards of terrestrial digital radio transmission. Compared with analog FM (frequency modulation) radio, it is more bandwidth efficient and offers greater possibilities when it comes to delivering content and forming an ensemble and multiplex. Currently, many countries worldwide, particularly European States, are still making adjustments in order to perform an efficient switchover from analog FM to digital DAB+ radio. This paper presents the current situation of the digital radio market as well as the results of a subjective quality evaluation study and questionnaire concerning broadcasting in both digital and analog techniques. It involves radio programs, transmitting both speech and music signals, simulcasted in DAB+ and FM standards. It also presents the development of the national multiplex. The results of this study may help both researchers and scientists as well as policy makers and professionals active in the field of broadcasting and electronic media and not to mention the consumption of multimedia content.

Relationships Across Clinical Measures of Vocal Quality and Functioning and Their Relationship With Patient Perception.

Purpose The purpose of this study was to investigate the relationships among subjective auditory-perceptual ratings of vocal quality, objective acoustic and aerodynamic measures of vocal function, and patient-perceived severity of their vocal complaint. Method This study was a retrospective chart review of adult patients evaluated at a single outpatient center over a 1.5-year time period. Twenty-two clinical objective and subjective measures of voice were extracted from 676 charts (310 males, 366 females). To identify the underlying concepts addressed in an initial voice assessment, principal component analyses were conducted for males and females to account for sex differences. Linear regression models were conducted to examine the relationship between the principal components and patient perceived severity. Results Seven principal components were identified for both sexes and accounted for 75% and 71% of the variance in the clinical measures, respectively. Of these seven principal components, only two predicted male patient perceived severity, which accounted for 22% of the variance. In contrast, four principal components predicted female patient perceived severity of their voice disorder and accounted for 19% of the variance. Conclusions The results highlight the underlying aspects of vocal quality and functioning that are evaluated during an initial assessment. Male and female patients differ in which of these components may contribute self-perceived severity of a voice disorder. Identifying these underlying components may support clinical decision making when developing a clinical protocol and highlights the overlap between patient concerns and clinical measures. Supplemental Material https://doi.org/10.23641/asha.16879603.

DCT Domain Detail Image Enhancement for More Resolved Images

This paper develops a detail image signal enhancement that makes images perceived as being clearer and more resolved and so more effective for higher resolution displays. We observe that the local variant signal enhancement makes images more vivid, and the more revealed granular signals harmonically embedded on the local variant signals make images more resolved. Based on this observation, we develop a method that not only emphasizes the local variant signals by scaling up the frequency energy in accordance with human visual perception, but also strengthens the granular signals by embedding the alpha-rooting enhanced frequency components. The proposed energy scaling method emphasizes the detail signals in texture images and rarely boosts noisy signals in plain images. In addition, to avoid the local ringing artifact, the proposed method adjusts the enhancement direction to be parallel to the underlying image signal direction. It was verified through subjective and objective quality evaluations that the developed method makes images perceived as clearer and highly resolved.

O033 Predicting subjective sleep quality using multi-day actigraphy data: A machine learning approach

Abstract Objectives Insomnia is diagnosed using clinical interview but actigraphy is often used as a consecutive multi-day measurement of activity-rest cycles to quantify sleep-wake periods. However, discrepancies between subjective complaints of insomnia and objective actigraphy measurement exist. The aims of the current study were to (i) predict subjective sleep quality using actigraphic data and, (ii) identify features of actigraphy that are associated with poor subjective sleep quality. Methods Actigraphy data were collected for 14-consecutive days with corresponding subjective sleep quality ratings from participants with Insomnia Disorder and healthy controls. We fitted multiple machine learning algorithms to determine the best performing method with the highest accuracy of predicting subjective quality rating using actigraphic data. Results We analysed a total of 1278 days of actigraphy and corresponding subjective sleep quality ratings from 86 insomnia disorder patients and 20 healthy controls. The k-neighbors classifier provided the best performance in predicting subjective sleep quality with an overall accuracy, sensitivity and specificity of 83%, 74% and 87% respectively, and an average AUC-ROC of 0.88. We also found that activity recorded in the early morning (04:00-08:00) and overnight periods (00:00-04:00) had the greatest influence on sleep quality scores, with poor sleep quality related to these periods.. Conclusions A machine learning model based on actigraphy time-series data successfully predicted self-reported sleep quality. This approach could facilitate clinician’s diagnostic capabilities and provide an objective marker of subjective sleep disturbance.

Beneficial loudspeaker/room/listener interactions

Sound reproduction of the highest quality requires an optimized combination of loudspeakers, rooms and listeners—electroacoustics, acoustics and psychoacoustics. Domestic and monitor loudspeakers have improved because of research investigating the physical sounds arriving at listeners in small rooms and correlating double-blind subjective ratings of sound quality with relevant anechoic measurements on loudspeakers. Loudspeakers designed using specific anechoic measurements and guidance (e.g., ANSI/CTA-2034-B) reliably yield high sound quality ratings in double-blind listening tests in normally reflective domestic rooms. The relative subjective ratings of loudspeakers remain substantially unchanged when comparison listening tests are conducted in rooms with very different acoustics, although the absolute sound quality has changed. Listeners clearly adapt to some of the essential perceptual characteristics of rooms. But there are limits. About 30% of subjective ratings of sound quality is attributable to bass quality. This is different for every arrangement of loudspeakers and listeners in every different room. Seat-to-seat variations at low frequencies are large. Absorption is traditionally used to damp bass resonances. However, for reproduced sound, multiple subwoofers, with or without signal processing, can manipulate room resonances. These schemes, with equalization, can substantially attenuate audible resonances while yielding much reduced seat-to-seat variation, using no passive acoustical devices.

Precision feeding gestating sows: effects on offspring growth performance and carcass and loin quality at slaughter.

A total of 601 pigs from 65 litters were used to determine the effects of closely meeting estimated daily Lys and energy requirements for sows during gestation for three consecutive parities on offspring postweaning growth performance and carcass and loin quality at slaughter. Sows were assigned a control (static diet composition; CON) or precision (individual daily blend of two diets to meet estimated Lys and energy requirements; PRE) feeding program between days 7 and 110 of gestation for three consecutive pregnancy cycles, starting with primiparous sows (parity 1: 12 CON and 12 PRE sows; parity 2: 8 CON and 13 PRE sows; parity 3: 8 CON and 12 PRE sows). At weaning (20 ± 2 d of age), up to 10 pigs per litter were randomly selected and placed in a pen (1 litter per pen). All pens received ad libitum access to commercial diets in six phases (four-phase nursery, grower, and finisher, respectively). Four pigs per pen were slaughtered at ~125 kg BW for evaluation of carcass characteristics and loin quality. The ADG and ADFI of offspring were not influenced by maternal feeding program in any parity during nursery phases I through III. During nursery phase IV, ADG and ADFI were greater for litters from PRE- vs. CON-fed sows (0.70 vs. 0.66 ± 0.03 and 1.15 vs. 1.08 ± 0.06 kg/d for ADG and ADFI, respectively; P < 0.05). The BW for litters from PRE- vs. CON-fed sows tended to be greater by day 66 of age (end of nursery period; 29.7 vs. 28.7 ± 1.1 kg; P = 0.076). Within the grower phase, litters from PRE-fed sows had a greater ADG in parity 2 but lower ADG in parity 3 vs. litters from CON-fed sows (0.99 vs. 0.94 and 0.93 vs. 1.01 ± 0.03 kg/d for parities 2 and 3, respectively; P < 0.05). No differences were observed for ADG or ADFI in the finisher phase or G:F in any phase for any parity. Loin eye area was smaller (52.2 vs. 55.0 ± 1.8 cm2; P < 0.05) for offspring from PRE- vs. CON-fed sows. In parity 2, carcass lean yield tended to be less for offspring from PRE- vs. CON-fed sows (58.6 vs. 59.6 ± 0.4%; P = 0.051). Minimal differences were observed for subjective and objective evaluations of loin quality. Closely meeting the estimated daily energy and Lys requirements for sows throughout gestation for three consecutive pregnancy cycles improved offspring growth performance (ADG and ADFI) in the final nursery stage, but generally did not affect growth performance in grower/finisher periods or carcass and loin quality at ~125 kg BW.

Combined Full-Reference Image Quality Metrics for Objective Assessment of Multiply Distorted Images

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.