Subjective and Objective Evaluation of Tone-Mapping and De-Ghosting Algorithms

With the increasing importance of high dynamic range (HDR) imaging and low availability of HDR displays, HDR cameras the need for efficient tone mapping, De-ghosting techniques is very crucial. However the tone mapping operators, De-Ghosting tend to introduce distortions in the HDR images, thus making it visually unpleasant in normal displays. Subjective evaluation of images is important for rating these algorithms as the users should be able to visualize the complete details present in both the brightly and poorly illuminated regions of the scene. To facilitate a systematic subjective study we have created a database of HDR images tone mapped, De-Ghosted using popular algorithms. We conducted a subjective study of the tone mapped images, computed objective scores by using some of the state-of-the-art no-reference low dynamic range image quality assessment algorithms and evaluated their performance. We show that a moderate and low correlation between objective and subjective scores indicates the need for the consideration of human perception in rating tone mapping operators and De-Ghosting algorithms

Kuvanlaatukokemuksen arvionnin instrumentit

This dissertation describes the instruments available for image quality evaluation, develops new methods for subjective image quality evaluation and provides image and video databases for the assessment and development of image quality assessment (IQA) algorithms. The contributions of the thesis are based on six original publications. The first publication introduced the VQone toolbox for subjective image quality evaluation. It created a platform for free-form experimentation with standardized image quality methods and was the foundation for later studies. The second publication focused on the dilemma of reference in subjective experiments by proposing a new method for image quality evaluation: the absolute category rating with dynamic reference (ACR-DR). The third publication presented a database (CID2013) in which 480 images were evaluated by 188 observers using the ACR-DR method proposed in the prior publication. Providing databases of image files along with their quality ratings is essential in the field of IQA algorithm development. The fourth publication introduced a video database (CVD2014) based on having 210 observers rate 234 video clips. The temporal aspect of the stimuli creates peculiar artifacts and degradations, as well as challenges to experimental design and video quality assessment (VQA) algorithms. When the CID2013 and CVD2014 databases were published, most state-of-the-art I/VQAs had been trained on and tested against databases created by degrading an original image or video with a single distortion at a time. The novel aspect of CID2013 and CVD2014 was that they consisted of multiple concurrent distortions. To facilitate communication and understanding among professionals in various fields of image quality as well as among non-professionals, an attribute lexicon of image quality, the image quality wheel, was presented in the fifth publication of this thesis. Reference wheels and terminology lexicons have a long tradition in sensory evaluation contexts, such as taste experience studies, where they are used to facilitate communication among interested stakeholders; however, such an approach has not been common in visual experience domains, especially in studies on image quality. The sixth publication examined how the free descriptions given by the observers influenced the ratings of the images. Understanding how various elements, such as perceived sharpness and naturalness, affect subjective image quality can help to understand the decision-making processes behind image quality evaluation. Knowing the impact of each preferential attribute can then be used for I/VQA algorithm development; certain I/VQA algorithms already incorporate low-level human visual system (HVS) models in their algorithms.Väitöskirja tarkastelee ja kehittää uusia kuvanlaadun arvioinnin menetelmiä, sekä tarjoaa kuva- ja videotietokantoja kuvanlaadun arviointialgoritmien (IQA) testaamiseen ja kehittämiseen. Se, mikä koetaan kauniina ja miellyttävänä, on psykologisesti kiinnostava kysymys. Työllä on myös merkitystä teollisuuteen kameroiden kuvanlaadun kehittämisessä. Väitöskirja sisältää kuusi julkaisua, joissa tarkastellaan aihetta eri näkökulmista. I. julkaisussa kehitettiin sovellus keräämään ihmisten antamia arvioita esitetyistä kuvista tutkijoiden vapaaseen käyttöön. Se antoi mahdollisuuden testata standardoituja kuvanlaadun arviointiin kehitettyjä menetelmiä ja kehittää niiden pohjalta myös uusia menetelmiä luoden perustan myöhemmille tutkimuksille. II. julkaisussa kehitettiin uusi kuvanlaadun arviointimenetelmä. Menetelmä hyödyntää sarjallista kuvien esitystapaa, jolla muodostettiin henkilöille mielikuva kuvien laatuvaihtelusta ennen varsinaista arviointia. Tämän todettiin vähentävän tulosten hajontaa ja erottelevan pienempiä kuvanlaatueroja. III. julkaisussa kuvaillaan tietokanta, jossa on 188 henkilön 480 kuvasta antamat laatuarviot ja niihin liittyvät kuvatiedostot. Tietokannat ovat arvokas työkalu pyrittäessä kehittämään algoritmeja kuvanlaadun automaattiseen arvosteluun. Niitä tarvitaan mm. opetusmateriaalina tekoälyyn pohjautuvien algoritmien kehityksessä sekä vertailtaessa eri algoritmien suorituskykyä toisiinsa. Mitä paremmin algoritmin tuottama ennuste korreloi ihmisten antamiin laatuarvioihin, sen parempi suorituskyky sillä voidaan sanoa olevan. IV. julkaisussa esitellään tietokanta, jossa on 210 henkilön 234 videoleikkeestä tekemät laatuarviot ja niihin liittyvät videotiedostot. Ajallisen ulottuvuuden vuoksi videoärsykkeiden virheet ovat erilaisia kuin kuvissa, mikä tuo omat haasteensa videoiden laatua arvioiville algoritmeille (VQA). Aikaisempien tietokantojen ärsykkeet on muodostettu esimerkiksi sumentamalla yksittäistä kuvaa asteittain, jolloin ne sisältävät vain yksiulotteisia vääristymiä. Nyt esitetyt tietokannat poikkeavat aikaisemmista ja sisältävät useita samanaikaisia vääristymistä, joiden interaktio kuvanlaadulle voi olla merkittävää. V. julkaisussa esitellään kuvanlaatuympyrä (image quality wheel). Se on kuvanlaadun käsitteiden sanasto, joka on kerätty analysoimalla 146 henkilön tuottamat 39 415 kuvanlaadun sanallista kuvausta. Sanastoilla on pitkät perinteet aistinvaraisen arvioinnin tutkimusperinteessä, mutta niitä ei ole aikaisemmin kehitetty kuvanlaadulle. VI. tutkimuksessa tutkittiin, kuinka arvioitsijoiden antamat käsitteet vaikuttavat kuvien laadun arviointiin. Esimerkiksi kuvien arvioitu terävyys tai luonnollisuus auttaa ymmärtämään laadunarvioinnin taustalla olevia päätöksentekoprosesseja. Tietoa voidaan käyttää esimerkiksi kuvan- ja videonlaadun arviointialgoritmien (I/VQA) kehitystyössä

Multimodal enhancement-fusion technique for natural images.

Masters Degree. University of KwaZulu-Natal, Durban.This dissertation presents a multimodal enhancement-fusion (MEF) technique for natural images. The MEF is expected to contribute value to machine vision applications and personal image collections for the human user. Image enhancement techniques and the metrics that are used to assess their performance are prolific, and each is usually optimised for a specific objective. The MEF proposes a framework that adaptively fuses multiple enhancement objectives into a seamless pipeline. Given a segmented input image and a set of enhancement methods, the MEF applies all the enhancers to the image in parallel. The most appropriate enhancement in each image segment is identified, and finally, the differentially enhanced segments are seamlessly fused. To begin with, this dissertation studies targeted contrast enhancement methods and performance metrics that can be utilised in the proposed MEF. It addresses a selection of objective assessment metrics for contrast-enhanced images and determines their relationship with the subjective assessment of human visual systems. This is to identify which objective metrics best approximate human assessment and may therefore be used as an effective replacement for tedious human assessment surveys. A subsequent human visual assessment survey is conducted on the same dataset to ascertain image quality as perceived by a human observer. The interrelated concepts of naturalness and detail were found to be key motivators of human visual assessment. Findings show that when assessing the quality or accuracy of these methods, no single quantitative metric correlates well with human perception of naturalness and detail, however, a combination of two or more metrics may be used to approximate the complex human visual response. Thereafter, this dissertation proposes the multimodal enhancer that adaptively selects the optimal enhancer for each image segment. MEF focusses on improving chromatic irregularities such as poor contrast distribution. It deploys a concurrent enhancement pathway that subjects an image to multiple image enhancers in parallel, followed by a fusion algorithm that creates a composite image that combines the strengths of each enhancement path. The study develops a framework for parallel image enhancement, followed by parallel image assessment and selection, leading to final merging of selected regions from the enhanced set. The output combines desirable attributes from each enhancement pathway to produce a result that is superior to each path taken alone. The study showed that the proposed MEF technique performs well for most image types. MEF is subjectively favourable to a human panel and achieves better performance for objective image quality assessment compared to other enhancement methods

Assessment of Quality of Experience of High Dynamic Range Images Using the EEG and Applications in Healthcare

File embargoed until 30.09.2021 at author's request.Recent years have witnessed the widespread application of High Dynamic Range (HDR) imaging, which like the Human Visual System (HVS), has the ability to capture a wide range of luminance values. Areas of application include home-entertainment, security, scientific imaging, video processing, computer graphics, multimedia communications, and healthcare. However, in practice, HDR content cannot be displayed in full on standard or low dynamic range (LDR) displays, and this diminishes the benefits of HDR technology for many users. To address this problem, Tone-Mapping Operators (TMO) are used to convert HDR images so that they can be displayed on low-dynamic-range displays and preserve as far as possible the perception of HDR. However, this may affect the visual Quality of Experience (QoE) of the end-user. QoE is a vital issue in image and video applications. It is important to understand how humans perceive quality in response to visual stimuli as this can potentially be exploited to develop and optimise image and video processing algorithms. Image consumption using mobile devices has become increasingly popular, given the availability of smartphones capable of producing and consuming HDR images along with advances in high-speed wireless communication networks. One of the most critical issues associated with mobile HDR image delivery services concerns how to maximise the QoE of the delivered content for users. An open research question therefore addresses how HDR images with different types of content perform on mobile phones. Traditionally, evaluation of the perceived quality of multimedia content is conducted using subjective opinion tests (i.e., explicitly), such as Mean Opinion Scores (MOS). However, it is difficult for the user to link the quality they are experiencing to the quality scale. Moreover, MOS does not give an insight into how the user feels at a physiological level in response to satisfaction or dissatisfaction with the perceived quality. To address this issue, measures that can be taken directly (implicitly) from the participant have now begun to attract interest. The electroencephalogram (EEG) is a promising approach that can be used to assess quality related processes implicitly. However, implicit QoE approaches are still at an early stage and further research is necessary to fully understand the nature of the recorded neural signals and their associations with user-perceived quality. Nevertheless, the EEG is expected to provide additional and complementary information that will aid understanding of the human perception of content. Furthermore, it has the potential to facilitate real-time monitoring of QoE without the need for explicit rating activities. The main aim of this project was therefore to assess the QoE of HDR images employing a physiological method and to investigate its potential application in the field of healthcare. This resulted in the following five main contributions to the research literature: 1. A detailed understanding of the relationship between the subjective and objective evaluation of the most popular TMOs used for colour and greyscale HDR images. Different mobile displays and resolutions were therefore presented under normal viewing conditions for the end-user with an LDR display as a reference. Preliminary results show that, compared to computer displays, small screen devices (SSDs) such as those used in smartphones impact the performance of TMOs in that a higher resolution gave more favourable MOS results. 2. The development of a novel Electrophysiology-based QoE assessment of HDR image quality that can be used to predict perceived image quality. This was achieved by investigating the relationships between changes in EEG features and subjective quality test scores (i.e. MOS) for HDR images viewed with SSD. 3. The development of a novel QoE prediction model, based on the above findings. The model can predict user acceptability and satisfaction for various mobile HDR image scenarios based on delta-beta coupling. Subjective quality tests were conducted to develop and evaluate the model, where the HDR image quality was predicted in terms of MOS. 4. The development of a new method of detecting a colour vision deficiency (CVD) using EEG and HDR images. The results suggest that this method may provide an accurate way to detect CVD with high sensitivity and specificity (close to 100%). Potentially, the method may facilitate the development of a low-cost tool suitable for CVD diagnosis in younger people. 5. The development of an approach that enhances the quality of dental x-ray images. This uses the concepts of QoE in HDR images without re-exposing patients to ionising radiation, thus improving patient care. Potentially, the method provides the basis for an intelligent model that accurately predicts the quality of dental images. Such a model can be embedded into a tool to automatically enhance poor quality dental images.Ministry of Higher Education and Scientific Research (MoHESR

Perceptual image quality assessment for various viewing conditions and display systems

From complete darkness to direct sunlight, real-world dis- plays operate in various viewing conditions often resulting in a non-optimal viewing experience. Most existing Image Quality Assessment (IQA) methods, however, assume ideal environments and displays, and thus cannot be used when viewing conditions differ from the standard. In this paper, we investigate the influence of ambient illumination level and display luminance on human perception of image quality. We conduct a psychophysical study to collect a novel dataset of over 10000 image quality preference judgments performed in illumination conditions ranging from 0 lux to 20000 lux. We also propose a perceptual IQA framework that allows most existing image quality metrics (IQM) to accurately predict image quality for a wide range of illumination conditions and display parameters 1 . Our analysis demonstrates strong cor- relation between human IQA and the predictions of our proposed framework combined with multiple prominent IQMs and across a wide range of luminance values

Subjective preference of light colour and LED lighting

The main objective of this work is to investigate the subjective preferences for lighting environments under different LED spectral power distributions (SPDs) and to analyse the different existing colour quality descriptors in order to recommend the best descriptor. An additional aim of the work is to find out the correlated colour temperature (CCT) and illuminance levels that users prefer for LED lighting. The experiments were conducted in lighting booths and in office rooms, where the subjective preferences for different LED light spectra were studied. In the lighting booth experiments, seven different LED SPDs were studied at CCTs of 2700 K, 4000 K and 6500 K at 500 lux. The study showed that the observers preferred the LED SPDs which increased the object chroma and colourfulness values (calculated in CIECAM02-UCS). Also, the preferred LED SPDs had higher values of reference-based metrics (such as colour quality scale (CQS) colour preference scale) and higher values of area-based metrics (such as CQS colour gamut scale or gamut area index (GAI)). The observers preferred the light sources at CCT of 4000 K and 6500 K over the CCT of 2700 K. The work was continued by simulation work and user acceptance studies to find out the simplified LED SPDs that the observers would prefer. The simulation results suggested that it is possible to generate simplified LED SPDs that have CQS Qp and CQS Qg values similar to those of the preferred complex SPDs that were generated by 9 to 11 different types of LEDs. The user acceptance studies conducted in the lighting booths also showed that the simplified LED SPDs using three different types of LEDs were preferred over complex LED SPD. Later, similar simplified LED SPDs were also studied in office rooms, and it was found that the observers preferred simplified LED SPDs over fluorescent lamp. The three different LED SPDs at each CCT of 4000 K and 6500 K were studied in the office room experiments. The observers preferred most the LED SPDs with high CQS Qp and CQS Qg or GAI values and least the LED SPDs that had the lowest CQS Qp and CQS Qg values. Also, the light sources (having high CQS Qp and CQS Qg) with negative Duv values were more preferred over light sources with positive Duv values maintaining the Duv values within the limit of ±0.0054. Moreover, for the office lighting, the observers preferred CCT of 4000 K over CCT of 6500 K at 500 lux. It was also found that the observers preferred the illuminance level of 500 lux over 300 lux. The results of the experiments conducted in the lighting booths to test the performance of different fidelity metrics showed that the CIE CRI, CRI2012 and CQS provide similar predictions for LED light sources that do not enhance the object chroma. It was found that the best prediction of colour fidelity was provided by CQS for LED light sources that enhance object chroma

Evaluation of changes in image appearance with changes in displayed image size

This research focused on the quantification of changes in image appearance when images are displayed at different image sizes on LCD devices. The final results provided in calibrated Just Noticeable Differences (JNDs) on relevant perceptual scales, allowing the prediction of sharpness and contrast appearance with changes in the displayed image size. A series of psychophysical experiments were conducted to enable appearance predictions. Firstly, a rank order experiment was carried out to identify the image attributes that were most affected by changes in displayed image size. Two digital cameras, exhibiting very different reproduction qualities, were employed to capture the same scenes, for the investigation of the effect of the original image quality on image appearance changes. A wide range of scenes with different scene properties was used as a test-set for the investigation of image appearance changes with scene type. The outcomes indicated that sharpness and contrast were the most important attributes for the majority of scene types and original image qualities. Appearance matching experiments were further conducted to quantify changes in perceived sharpness and contrast with respect to changes in the displayed image size. For the creation of sharpness matching stimuli, a set of frequency domain filters were designed to provide equal intervals in image quality, by taking into account the system’s Spatial Frequency Response (SFR) and the observation distance. For the creation of contrast matching stimuli, a series of spatial domain S-shaped filters were designed to provide equal intervals in image contrast, by gamma adjustments. Five displayed image sizes were investigated. Observers were always asked to match the appearance of the smaller version of each stimulus to its larger reference. Lastly, rating experiments were conducted to validate the derived JNDs in perceptual quality for both sharpness and contrast stimuli. Data obtained by these experiments finally converted into JND scales for each individual image attribute. Linear functions were fitted to the final data, which allowed the prediction of image appearance of images viewed at larger sizes than these investigated in this research

Individualized Models of Colour Differentiation through Situation-Specific Modelling

In digital environments, colour is used for many purposes: for example, to encode information in charts, signify missing field information on websites, and identify active windows and menus. However, many people have inherited, acquired, or situationally-induced Colour Vision Deficiency (CVD), and therefore have difficulties differentiating many colours. Recolouring tools have been developed that modify interface colours to make them more differentiable for people with CVD, but these tools rely on models of colour differentiation that do not represent the majority of people with CVD. As a result, existing recolouring tools do not help most people with CVD. To solve this problem, I developed Situation-Specific Modelling (SSM), and applied it to colour differentiation to develop the Individualized model of Colour Differentiation (ICD). SSM utilizes an in-situ calibration procedure to measure a particular user’s abilities within a particular situation, and a modelling component to extend the calibration measurements into a full representation of the user’s abilities. ICD applies in-situ calibration to measuring a user’s unique colour differentiation abilities, and contains a modelling component that is capable of representing the colour differentiation abilities of almost any individual with CVD. This dissertation presents four versions of the ICD and one application of the ICD to recolouring. First, I describe the development and evaluation of a feasibility implementation of the ICD that tests the viability of the SSM approach. Second, I present revised calibration and modelling components of the ICD that reduce the calibration time from 32 minutes to two minutes. Next, I describe the third and fourth ICD versions that improve the applicability of the ICD to recolouring tools by reducing the colour differentiation prediction time and increasing the power of each prediction. Finally, I present a new recolouring tool (ICDRecolour) that uses the ICD model to steer the recolouring process. In a comparative evaluation, ICDRecolour achieved 90% colour matching accuracy for participants – 20% better than existing recolouring tools – for a wide range of CVDs. By modelling the colour differentiation abilities of a particular user in a particular environment, the ICD enables the extension of recolouring tools to helping most people with CVD, thereby reducing the difficulties that people with CVD experience when using colour in digital environments

Tone mapping HDR panoramas for viewing in Head Mounted Displays

Head-mounted displays enable a user to view a complete environment as if he/she was there; providing an immersive experience. However, the lighting in a full environment can vary significantly. Panoramic images captured with conventional, Low Dynamic Range (LDR), imaging of scenes with a large range of lighting conditions, can include areas of under- or over-exposed pixels. High Dynamic Range (HDR) imaging, on the other hand, is able to capture the full range of detail in a scene. However, HMDs are not currently HDR and thus the HDR panorama needs to be tone mapped before it can be displayed on the LDR HMD. While a large number of tone mapping operators have been proposed in the last 25 years, these were not designed for panoramic images, or for use with HMDs. This paper undertakes a two part subjective study to investigate which of the current, state-of-the-art tone mappers is most suitable for use with HMD