Colour image Enhancement using Background Brightness Preserving Histogram Equalization

Histogram Equalization (HE) is generally used to upgrade the image contrast yet it has a tendency to over enhance the image background brightness. BBHE (Bi Histogram Equalization) has broken down and proposed scientifically that it may be preserved original brightness to a certain limit. On the other hand, still cases are not handled well by the BBHE, as they are requiring preservation of higher degree. Particular paper has proposed novel augmentation of BBHE, which alluded to as the MMBEBHE (Minimum Mean Brightness Error Bi Histogram Equalization) to give maximum brightness preservation. BBHE isolates the input image's histogram into two in depend on input mean before leveling with them freely. Enhancement schemes have been presented with minimum defects of the conventional HE, yet the over enhance of the background brightness is still self-evident. A novel methodology of nonlinear HE is displayed, which has the capacity to enhance the image contrast, while preserving the background brightness for images with very much characterized background brightness

High-Brightness Image Enhancement Algorithm

In this paper, we introduce a tone mapping algorithm for processing high-brightness video images. This method can maximally recover the information of high-brightness areas and preserve detailed information. Along with benchmark data, real-life and practical application data were taken to test the proposed method. The experimental objects were license plates. We reconstructed the image in the RGB channel, and gamma correction was carried out. After that, local linear adjustment was completed through a tone mapping window to restore the detailed information of the high-brightness region. The experimental results showed that our algorithm could clearly restore the details of high-brightness local areas. The processed image conformed to the visual effect observed by human eyes but with higher definition. Compared with other algorithms, the proposed algorithm has advantages in terms of both subjective and objective evaluation. It can fully satisfy the needs in various practical applications

Objective Quality Assessment and Optimization for High Dynamic Range Image Tone Mapping

Tone mapping operators aim to compress high dynamic range (HDR) images to low dynamic range ones so as to visualize HDR images on standard displays. Most existing works were demonstrated on specific examples without being thoroughly tested on well-established and subject-validated image quality assessment models. A recent tone mapped image quality index (TMQI) made the first attempt on objective quality assessment of tone mapped images. TMQI consists of two fundamental building blocks: structural fidelity and statistical naturalness. In this thesis, we propose an enhanced tone mapped image quality index (eTMQI) by 1) constructing an improved nonlinear mapping function to better account for the local contrast visibility of HDR images and 2) developing an image dependent statistical naturalness model to quantify the unnaturalness of tone mapped images based on a subjective study. Experiments show that the modified structural fidelity and statistical naturalness terms in eTMQI better correlate with subjective quality evaluations. Furthermore, we propose an iterative optimization algorithm for tone mapping. The advantages of this algorithm are twofold: 1) eTMQI and TMQI can be compared in a more straightforward way; 2) better quality tone mapped images can be automatically generated by using eTMQI as the optimization goal. Numerical and subjective experiments demonstrate that eTMQI is a superior objective quality assessment metric for tone mapped images and consistently outperforms TMQI

Processeurs embarqués configurables pour la reproduction de tons

RÉSUMÉ Les images à grande gamme dynamique (HDR) peuvent capturer les détails d’une scène à la fois dans les zones les plus claires et les zones ombragées, en imitant les capacités du système visuel humain. La reproduction de tons (TM) vise à adapter les images HDR aux dispositifs d’affichage traditionnels. La première partie de ce travail s’occupe d’une application des algorithmes de reproduction de tons : l’amélioration du contraste. Nous avons effectué une comparaison de plusieurs méthodes de pointe d’ajustement du contraste, y compris deux opérateurs de TM. Cette analyse comparative a été mise en oeuvre dans le contexte d’applications de surveillance lorsque les vidéos sont prises dans des conditions d’éclairage faibles. La qualité de l’image a été évaluée en utilisant des métriques objectives comme le contraste d’intensités et l’erreur de la brillance, et via une évaluation subjective. De plus, la performance a été mesurée en fonction du temps d’exécution. Les résultats expérimentaux montrent qu’une technique récente basée sur une modification de l’histogramme présente un meilleur compromis si les deux critères sont considérés. Les algorithmes de TM imposent habituellement des besoins élevés en ressources de calcul. En conséquence, ces algorithmes sont normalement implémentés sur des processeurs à usage général puissants et des processeurs graphiques. Ces plateformes ne peuvent pas toujours satisfaire les contraintes de performance, de surface, de consommation de puissance et de flexibilité imposées par le domaine des systèmes embarqués. Même si ces exigences sont souvent contradictoires, les processeurs à jeu d’instructions spécialisées (ASIP) deviennent une alternative d’implémentation intéressante. Les ASIP peuvent fournir un compromis entre l’efficacité d’une solution matérielle dédiée et la flexibilité associée à une solution logicielle programmable. La deuxième partie de ce mémoire présente la conception et l’implémentation d’un processeur spécialisé pour un algorithme global de TM. Nous avons analysé l’algorithme entier afin d’estimer les besoins en données et en calculs. Trois instructions spécialisées ont été proposées : pour calculer les valeurs de la luminance, du logarithme et de la luminance maximale. En utilisant un langage de description architecturale, les instructions spécialisées ont été ajoutées à un processeur similaire à un RISC de 32 bits. Le logarithme a été calculé à l’aide d’une technique spécifique à faible coût basée sur une approximation de Mitchell améliorée. Les résultats expérimentaux démontrent une augmentation de la performance de 169% si les trois instructions y sont rajoutées, avec un coût matériel supplémentaire de seulement 22%. Finalement, comme les algorithmes globaux de TM peuvent ne pas préserver d’importants contrastes locaux, nous avons conçu et implémenté un autre ASIP pour un algorithme local. Des instructions spécialisées pour accélérer une pyramide gaussienne modifiée ont été ajoutées à un processeur configurable et extensible, semblable à un RISC de 32 bits. Les différents niveaux de la pyramide ont été calculés en utilisant un noyau gaussien 2D unique dans un processus itératif. Les résultats montrent un facteur d’accélération de 12,3× pour le calcul de la pyramide, ce qui implique une amélioration de la performance de 50% pour l’algorithme local. Ce processeur spécialisé requiert une augmentation de la surface de 19% par rapport à la configuration de base. ---------ABSTRACT High dynamic range (HDR) images can capture the details of a scene in both highlights and shadows, imitating the capabilities of the human visual system. Tone mapping (TM) aims to adapt HDR images to conventional display devices. The first part of this work deals with an application of tone mapping algorithms: contrast enhancement. We compare several state-of-the-art contrast adjustment methods, including two TM operators. This comparative analysis was conducted in the context of surveillance applications when videos are taken in poor lighting conditions. Image quality was evaluated by means of objective metrics such as intensity contrast and brightness error, and by subjective assessment. Moreover, performance was measured based on execution time. Experimental results show that a recent technique based on histogram modification presents a better trade-off considering both aspects. TM algorithms usually impose high demands on computational resources. As a result, they are usually implemented on powerful general purpose processors and graphics processing units. Such platforms may not meet performance, area, power consumption and flexibility constraints imposed by the embedded system domain. These requirements are often contradictory, and application-specific instruction-set processors (ASIPs) become an interesting implementation alternative. ASIPs can provide a trade-off between the efficiency of a dedicated hardware solution and the flexibility associated with a software programmable solution. The second part of this master thesis presents the design and implementation of a customized processor for a global TM algorithm. We analyzed the whole algorithm to estimate the data and computational requirements. Three custom instructions were proposed: to calculate luminance, logarithm and maximum luminance values. Using an architecture description language, the custom instructions were added to a 32-bit RISC-based processor. The logarithm was computed using a specific low cost technique based on an improved Mitchell approximation. Experimental results demonstrate a 169% performance improvement when adding all three instructions, with a hardware overhead of only 22%. Finally, as global TM algorithms may not preserve important local contrasts, we designed and implemented another ASIP for a local algorithm. Custom instructions to accelerate a modified Gaussian pyramid were added to a configurable and extensible 32-bit RISC-like processor. The different pyramid levels were computed using a unique 2D Gaussian kernel in an iterative process. Results show a speedup factor of 12,3× for the pyramid computation, which implies a 50% performance improvement for the local algorithm. This customized processor requires a 19% area increase compared to the base configuration

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

Tone mapping in video conference systems

Normal sensors are able to only capture a limited dynamic range. In scenes with large dynamic range, such as situations with both dark indoor and bright outdoor parts, the image will get either over- or under exposed if the exposure is not perfect. Producing high dynamic range (HDR) images will capture the full dynamic range of the scene. There are two main ways of producing HDR images. One combines multiple exposures with a low dynamic range (LDR) sensor. Another is to use a sensors which are able to capture a higher dynamic range, so called wide dynamic range sensors.Multiple exposures with a single low dynamic range sensor, is not suitable for real time video because this technique have large problems with movement. Wide dynamic range sensors only require one exposure, but these have difficulties in normal situations were LDR sensors are sufficient. A type of algorithms called tone mapping are used to reduce the high dynamic range image to at the limitations of normal monitors. Simulations show that using these algorithms on low dynamic range images will change the illumination of the scene, solving the problem. Tone mapping algorithms presented in the literature are software algorithms. Two groups of algorithms exist; local and global tone mappers. Local algorithms are time consuming, and require large amounts of memory. They are not suitable for real time implementations since they rely on filtering operations for each pixel. Global algorithms, does not rely on filtering and are less time consuming. A precomputed curve is used to map the pixels to new values. This makes the global algorithms more suitable for video. A reduced tone mapping system is presented. This reduction results in a segmented curve, which drastically reduces the memory required for defining the curve. It also makes it feasible to control temporal changes. The reduced system has been successfully implemented, achieving sufficient frequencies to be part of a real time system

Local tone mapping operator for detail preserving reproduction of high dynamic range images.

Opseg osvetljaja koji se javlja u prirodnim scenama uveliko prevazilazi mogućnosti standardnih uređaja za snimanje i reprodukciju slike. Ljudski vizuelni sistem je evoluirao, tako da omogući efikasno funkcionisanje i percepciju detalja u uslovima velike promene osvetljaja. Kako bi se omogućila što realnija reprodukcija slika i video sadržaja, potrebno je obezbediti mogućnost snimanja i reprodukcije što šireg dinamičkog opsega osvetljaja. Razvoj tehnika za snimanje je napredovao i danas postoji mogućnost snimanja celokupnog dinamičkog opsega osvetljaja scene korišćenjem standardnih senzora. Razvoj displeja je međutim napredovao sporije i većina displeja koji su danas u upotrebi ima skroman dinamički opseg osvetljaja. Operator za redukciju dinamičkog opsega predstavlja ključnu komponentu sistema za reprodukciju scena širokog dinamičkog opsega (HDR), na standardnim displejima nižeg dinamičkog opsega (LDR)...Light intensity variations in natural scenes greatly exceed the capabillities of standard imaging and display devices. The human visual system has evolved to deal with these lightning conditions and enable efficient perception of details. In order to enable realistic reproduction of natural images and video, it is necessary to develop techniques and devices for capturing and reproduction of the high dynamic range content. Capturing techniques have evolved and now it is possible to capture entire dynamic range of the scene using standard sensors. The development of displays, however, has progressed more slowly and most of the displays that are used today exhibits modest dynamic range capabilities. Tone mapping operator is a key component that enables reproduction of the high dynamic range (HDR) images on the low dynamic range (LDR) displays..