Digital Video Image Quality

Optical physic

Image interpolation via regularized local linear regression

In this paper, we present an efficient image interpolation scheme by using regularized local linear regression (RLLR). On one hand, we introduce a robust estimator of local image structure based on moving least squares, which can efficiently handle the statistical outliers compared with ordinary least squares based methods. On the other hand, motivated by recent progress on manifold based semi-supervise learning, the intrinsic manifold structure is explicitly considered by making use of both measured and unmeasured data points. In particular, the geometric structure of the marginal probability distribution induced by unmeasured samples is incorporated as an additional locality preserving constraint. The optimal model parameters can be obtained with a closed-form solution by solving a convex optimization problem. Experimental results demonstrate that our method outperform the existing methods in both objective and subjective visual quality over a wide range of test images. ? 2010 IEEE.EI

Perceptual quality assessment and processing for visual signals.

視覺信號，包括圖像，視頻等，在采集，壓縮，存儲，傳輸，重新生成的過程中都會被各種各樣的噪聲所影響，因此他們的主觀質量也就會降低。所以，主觀視覺質量在現今的視覺信號處理跟通訊系統中起到了很大的作用。這篇畢業論文主要討論質量評價的算法設計，以及這些衡量標準在視覺信號處理上的應用。這篇論文的工作主要包括以下五個方面。第一部分主要集中在具有完全套考原始圖像的圖像質量評價。首先我們研究人類視覺系統的特征。具體說來，視覺在結構化失真上面的水平特性和顯著特征會被建模然后應用到結構相似度(SSIM)這個衡量標準上。實驗顯示我們的方法明顯的提高了衡量標準典主觀評價的相似度。由這個質量衡量標準的啟發，我們設計了一個主觀圖像壓縮的方法。其中我們提出了一個自適應的塊大小的超分辨率算法指導的下采樣的算法。實驗結果證明提出的圖像壓縮算法無論在主觀還是在客觀層面都構建了高質量的圖像。第二個部分的工作主要討論具有完全參考原始視頻的視頻質量評價。考慮到人類視覺系統的特征，比如時空域的對此敏感函數，眼球的移動，紋理的遮掩特性，空間域的一致性，時間域的協調性，不同塊變換的特性，我們設計了一個自適應塊大小的失真閾值的模型。實驗證明，我們提出的失真閾值模型能夠更精確的描迷人類視覺系統的特性。基于這個自適應塊大小的失真閾值模型，我們設計了一個簡單的主觀質量評價標準。在公共的圓像以及視頻的主觀數據庫上的測試結果證明了這個簡單的評價標準的有效性。因此，我們把這個簡單的質量標準應用于視頻編碼系統中。它可以在同樣的碼率下提供更高主觀質量的視頻。第三部分我們討論具有部分參考信息的圖像質量評價。我們通過描迷重組后的離散余弦變換域的系數的統計分布來衡量圖像的主觀質量。提出的評價標準發掘了相鄰的離散余弦系數的相同統計特性，相鄰的重組離散余弦系數的互信息，以及圖像的能量在不同頻率下的分布。實驗結果證明我們提出的質量標準河以超越其他的具有部分參考信息的質量評價標準，甚至還超過了具有完全參考信息的質量評價標準。而且，提取的特征很容易被編碼以及隱藏到圖像中以便于在圖像通訊中進行質量監控。第四部分我們討論具有部分參考信息的視頻質量評價。我們提取的特征可以很好的描迷空間域的信息失，和時間域的相鄰兩幀間的直方圖的統計特性。在視頻主觀質量的數據庫上的實驗結果，也證明了提出的方法河以超越其他代表性的視頻質量評價標準，甚至是具有完全參考信息的質量評價標準， 譬如PSNR以及SSIM 。我們的方法只需要很少的特征來描迷每一幀視頻圖像。對于每一幀圖像，一個特征用于描迷空間域的特點，另外三個特征用于描述時間域的特點。考慮到計算的復雜度以及壓縮特征所需要的碼率，提出的方法河以很簡單的在視頻的傳輸過程中監控視頻的質量。之前的四部分提到的主觀質量評價標準主要集中在傳統的失真上面， 譬如JPEG 圖像壓縮， H.264視頻壓縮。在最后一部分，我們討論在圖像跟視頻的retargeting過程中的失真。現如今，隨著消費者電子的發展，視覺信號需要在不同分辨率的顯示設備上進行通訊交互。因此， retargeting的算法把同一個原始圖像適應于不同的分辨率的顯示設備。這樣的過程就會引入圖像的失真。我們研究了對于retargeting圖像主觀質量的測試者的分數，從三個方面進行討論測試者對于retargeting圖像失真的反應.圖像retargeting的尺度，圖像retargeting的算法，原始圖像的內容特性。通過大量的主觀實驗測試，我們構建了一個關于圖像retargeting的主觀數據庫。基于這個主觀數據庫，我們評價以及分析了幾個具有代表性的質量評價標準。Visual signals, including images, videos, etc., are affected by a wide variety of distortions during acquisition, compression, storage, processing, transmission, and reproduction processes, which result in perceptual quality degradation. As a result, perceptual quality assessment plays a very important role in today's visual signal processing and communication systems. In this thesis, quality assessment algorithms for evaluating the visual signal perceptual quality, as well as the applications on visual signal processing and communications, are investigated. The work consists of five parts as briefly summarized below.The first part focuses on the full-reference (FR) image quality assessment. The properties of the human visual system (HVS) are firstly investigated. Specifically, the visual horizontal effect (HE) and saliency properties over the structural distortions are modelled and incorporated into the structure similarity index (SSIM). Experimental results show significantly improved performance in matching the subjective ratings. Inspired by the developed FR image metric, a perceptual image compression scheme is developed, where the adaptive block-based super-resolution directed down-sampling is proposed. Experimental results demonstrated that the proposed image compression scheme can produce higher quality images in terms of both objective and subjective qualities, compared with the existing methods.The second part concerns the FR video quality assessment. The adaptive block-size transform (ABT) based just-noticeable difference (JND) for visual signals is investigated by considering the HVS characteristics, e.g., spatio-temporal contrast sensitivity function (CSF), eye movement, texture masking, spatial coherence, temporal consistency, properties of different block-size transforms, etc. It is verified that the developed ABT based JND can more accurately depict the HVS property, compared with the state-of-the-art JND models. The ABT based JND is thereby utilized to develop a simple perceptual quality metric for visual signals. Validations on the image and video subjective quality databases proved its effectiveness. As a result, the developed perceptual quality metric is employed for perceptual video coding, which can deliver video sequences of higher perceptual quality at the same bit-rates.The third part discusses the reduced-reference (RR) image quality assessment, which is developed by statistically modelling the coe cient distribution in the reorganized discrete cosine transform (RDCT) domain. The proposed RR metric exploits the identical statistical nature of the adjacent DCT coefficients, the mutual information (MI) relationship between adjacent RDCT coefficients, and the image energy distribution among different frequency components. Experimental results demonstrate that the proposed metric outperforms the representative RR image quality metrics, and even the FR quality metric, i.e., peak signal to noise ratio (PSNR). Furthermore, the extracted RR features can be easily encoded and embedded into the distorted images for quality monitoring during image communications.The fourth part investigates the RR video quality assessment. The RR features are extracted to exploit the spatial information loss and the temporal statistical characteristics of the inter-frame histogram. Evaluations on the video subjective quality databases demonstrate that the proposed method outperforms the representative RR video quality metrics, and even the FR metrics, such as PSNR, SSIM in matching the subjective ratings. Furthermore, only a small number of RR features is required to represent the original video sequence (each frame requires only 1 and 3 parameters to depict the spatial and temporal characteristics, respectively). By considering the computational complexity and the bit-rates for extracting and representing the RR features, the proposed RR quality metric can be utilized for quality monitoring during video transmissions, where the RR features for perceptual quality analysis can be easily embedded into the videos or transmitted through an ancillary data channel.The aforementioned perceptual quality metrics focus on the traditional distortions, such as JPEG image compression noise, H.264 video compression noise, and so on. In the last part, we investigate the distortions introduced during the image and video retargeting process. Nowadays, with the development of the consumer electronics, more and more visual signals have to communicate between different display devices of different resolutions. The retargeting algorithm is employed to adapt a source image of one resolution to be displayed in a device of a different resolution, which may introduce distortions during the retargeting process. We investigate the subjective responses on the perceptual qualities of the retargeted images, and discuss the subjective results from three perspectives, i.e., retargeting scales, retargeting methods, and source image content attributes. An image retargeting subjective quality database is built by performing a large-scale subjective study of image retargeting quality on a collection of retargeted images. Based on the built database, several representative quality metrics for retargeted images are evaluated and discussed.Detailed summary in vernacular field only.Detailed summary in vernacular field only.Detailed summary in vernacular field only.Detailed summary in vernacular field only.Detailed summary in vernacular field only.Detailed summary in vernacular field only.Ma, Lin."December 2012."Thesis (Ph.D.)--Chinese University of Hong Kong, 2013.Includes bibliographical references (leaves 185-197).Abstract also in Chinese.Dedication --- p.iiAcknowledgments --- p.iiiAbstract --- p.viiiPublications --- p.xiNomenclature --- p.xviiContents --- p.xxivList of Figures --- p.xxviiiList of Tables --- p.xxxChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation and Objectives --- p.1Chapter 1.2 --- Subjective Perceptual Quality Assessment --- p.5Chapter 1.3 --- Objective Perceptual Quality Assessment --- p.10Chapter 1.3.1 --- Visual Modelling Approach --- p.10Chapter 1.3.2 --- Engineering Modelling Approach --- p.15Chapter 1.3.3 --- Perceptual Subjective Quality Databases --- p.19Chapter 1.3.4 --- Performance Evaluation --- p.21Chapter 1.4 --- Thesis Contributions --- p.22Chapter 1.5 --- Organization of the Thesis --- p.24Chapter I --- Full Reference Quality Assessment --- p.26Chapter 2 --- Full Reference Image Quality Assessment --- p.27Chapter 2.1 --- Visual Horizontal Effect for Image Quality Assessment --- p.27Chapter 2.1.1 --- Introduction --- p.27Chapter 2.1.2 --- Proposed Image Quality Assessment Framework --- p.28Chapter 2.1.3 --- Experimental Results --- p.34Chapter 2.1.4 --- Conclusion --- p.36Chapter 2.2 --- Image Compression via Adaptive Block-Based Super-Resolution Directed Down-Sampling --- p.37Chapter 2.2.1 --- Introduction --- p.37Chapter 2.2.2 --- The Proposed Image Compression Framework --- p.38Chapter 2.2.3 --- Experimental Results --- p.42Chapter 2.2.4 --- Conclusion --- p.45Chapter 3 --- Full Reference Video Quality Assessment --- p.46Chapter 3.1 --- Adaptive Block-size Transform based Just-Noticeable Dfference Model for Visual Signals --- p.46Chapter 3.1.1 --- Introduction --- p.46Chapter 3.1.2 --- JND Model based on Transforms of Different Block Sizes --- p.48Chapter 3.1.3 --- Selection Strategy Between Transforms of Different Block Sizes --- p.53Chapter 3.1.4 --- JND Model Evaluation --- p.56Chapter 3.1.5 --- Conclusion --- p.60Chapter 3.2 --- Perceptual Quality Assessment --- p.60Chapter 3.2.1 --- Experimental Results --- p.62Chapter 3.2.2 --- Conclusion --- p.64Chapter 3.3 --- Motion Trajectory Based Visual Saliency for Video Quality Assessment --- p.65Chapter 3.3.1 --- Motion Trajectory based Visual Saliency for VQA --- p.66Chapter 3.3.2 --- New Quaternion Representation (QR) for Each frame --- p.66Chapter 3.3.3 --- Saliency Map Construction by QR --- p.67Chapter 3.3.4 --- Incorporating Visual Saliency with VQAs --- p.68Chapter 3.3.5 --- Experimental Results --- p.69Chapter 3.3.6 --- Conclusion --- p.72Chapter 3.4 --- Perceptual Video Coding --- p.72Chapter 3.4.1 --- Experimental Results --- p.75Chapter 3.4.2 --- Conclusion --- p.76Chapter II --- Reduced Reference Quality Assessment --- p.77Chapter 4 --- Reduced Reference Image Quality Assessment --- p.78Chapter 4.1 --- Introduction --- p.78Chapter 4.2 --- Reorganization Strategy of DCT Coefficients --- p.81Chapter 4.3 --- Relationship Analysis of Intra and Inter RDCT subbands --- p.83Chapter 4.4 --- Reduced Reference Feature Extraction in Sender Side --- p.88Chapter 4.4.1 --- Intra RDCT Subband Modeling --- p.89Chapter 4.4.2 --- Inter RDCT Subband Modeling --- p.91Chapter 4.4.3 --- Image Frequency Feature --- p.92Chapter 4.5 --- Perceptual Quality Analysis in the Receiver Side --- p.95Chapter 4.5.1 --- Intra RDCT Feature Difference Analysis --- p.95Chapter 4.5.2 --- Inter RDCT Feature Difference Analysis --- p.96Chapter 4.5.3 --- Image Frequency Feature Difference Analysis --- p.96Chapter 4.6 --- Experimental Results --- p.98Chapter 4.6.1 --- Efficiency of the DCT Reorganization Strategy --- p.98Chapter 4.6.2 --- Performance of the Proposed RR IQA --- p.99Chapter 4.6.3 --- Performance of the Proposed RR IQA over Each Individual Distortion Type --- p.105Chapter 4.6.4 --- Statistical Significance --- p.107Chapter 4.6.5 --- Performance Analysis of Each Component --- p.109Chapter 4.7 --- Conclusion --- p.111Chapter 5 --- Reduced Reference Video Quality Assessment --- p.113Chapter 5.1 --- Introduction --- p.113Chapter 5.2 --- Proposed Reduced Reference Video Quality Metric --- p.114Chapter 5.2.1 --- Reduced Reference Feature Extraction from Spatial Perspective --- p.116Chapter 5.2.2 --- Reduced Reference Feature Extraction from Temporal Perspective --- p.118Chapter 5.2.3 --- Visual Quality Analysis in Receiver Side --- p.121Chapter 5.3 --- Experimental Results --- p.123Chapter 5.3.1 --- Consistency Test of the Proposed RR VQA over Compressed Video Sequences --- p.124Chapter 5.3.2 --- Consistency Test of the Proposed RR VQA over Video Sequences with Simulated Distortions --- p.126Chapter 5.3.3 --- Performance Evaluation of the Proposed RR VQA on Compressed Video Sequences --- p.129Chapter 5.3.4 --- Performance Evaluation of the Proposed RR VQA on Video Sequences Containing Transmission Distortions --- p.133Chapter 5.3.5 --- Performance Analysis of Each Component --- p.135Chapter 5.4 --- Conclusion --- p.137Chapter III --- Retargeted Visual Signal Quality Assessment --- p.138Chapter 6 --- Image Retargeting Perceptual Quality Assessment --- p.139Chapter 6.1 --- Introduction --- p.139Chapter 6.2 --- Preparation of Database Building --- p.142Chapter 6.2.1 --- Source Image --- p.142Chapter 6.2.2 --- Retargeting Methods --- p.143Chapter 6.2.3 --- Subjective Testing --- p.146Chapter 6.3 --- Data Processing and Analysis for the Database --- p.150Chapter 6.3.1 --- Processing of Subjective Ratings --- p.150Chapter 6.3.2 --- Analysis and Discussion of the Subjective Ratings --- p.153Chapter 6.4 --- Objective Quality Metric for Retargeted Images --- p.162Chapter 6.4.1 --- Quality Metric Performances on the Constructed Image Retargeting Database --- p.162Chapter 6.4.2 --- Subjective Analysis of the Shape Distortion and Content Information Loss --- p.165Chapter 6.4.3 --- Discussion --- p.167Chapter 6.5 --- Conclusion --- p.169Chapter 7 --- Conclusions --- p.170Chapter 7.1 --- Conclusion --- p.170Chapter 7.2 --- Future Work --- p.173Chapter A --- Attributes of the Source Image --- p.176Chapter B --- Retargeted Image Name and the Corresponding Number --- p.179Chapter C --- Source Image Name and the Corresponding Number --- p.183Bibliography --- p.18

Video QoS/QoE over IEEE802.11n/ac: A Contemporary Survey

The demand for video applications over wireless networks has tremendously increased, and IEEE 802.11 standards have provided higher support for video transmission. However, providing Quality of Service (QoS) and Quality of Experience (QoE) for video over WLAN is still a challenge due to the error sensitivity of compressed video and dynamic channels. This thesis presents a contemporary survey study on video QoS/QoE over WLAN issues and solutions. The objective of the study is to provide an overview of the issues by conducting a background study on the video codecs and their features and characteristics, followed by studying QoS and QoE support in IEEE 802.11 standards. Since IEEE 802.11n is the current standard that is mostly deployed worldwide and IEEE 802.11ac is the upcoming standard, this survey study aims to investigate the most recent video QoS/QoE solutions based on these two standards. The solutions are divided into two broad categories, academic solutions, and vendor solutions. Academic solutions are mostly based on three main layers, namely Application, Media Access Control (MAC) and Physical (PHY) which are further divided into two major categories, single-layer solutions, and cross-layer solutions. Single-layer solutions are those which focus on a single layer to enhance the video transmission performance over WLAN. Cross-layer solutions involve two or more layers to provide a single QoS solution for video over WLAN. This thesis has also presented and technically analyzed QoS solutions by three popular vendors. This thesis concludes that single-layer solutions are not directly related to video QoS/QoE, and cross-layer solutions are performing better than single-layer solutions, but they are much more complicated and not easy to be implemented. Most vendors rely on their network infrastructure to provide QoS for multimedia applications. They have their techniques and mechanisms, but the concept of providing QoS/QoE for video is almost the same because they are using the same standards and rely on Wi-Fi Multimedia (WMM) to provide QoS

Contribución a los modelos de estimación de la calidad percibida en servicios de vídeo sobre Internet mediante parámetros objetivos

En los últimos años el consumo de servicios de vídeo se ha incrementado de forma notable y se espera que dicha tendencia continúe en los próximos años. Los servicios de streaming de vídeo Over-The-Top (OTT), en los que se centra esta tesis, constituyen uno de los principales motores de dicho crecimiento. A diferencia de los servicios Internet Protocol Television (IPTV), que utilizan una red controlada en la que se pueden implementar mecanismos de Quality of Service (QoS), los servicios de streaming de vídeo OTT se prestan sobre Internet, por lo que llevan asociados interesantes desafíos desde un punto de vista técnico. Uno de los mayores desafíos técnicos a los que se enfrentan los servicios de streaming de vídeo OTT es mantener un nivel de Quality of Experience (QoE) que satisfaga a sus usuarios, por lo que es necesario contar con técnicas y herramientas que permitan monitorizar la calidad percibida por los usuarios de estos servicios. El streaming de vídeo OTT supone un cambio de filosofía en comparación con otras técnicas de streaming más tradicionales como RTP/RTSP. Los servicios de vídeo OTT suelen seguir el paradigma Dynamic Adaptive Streaming over HTTP (DASH), que se basa en sustituir los servidores de streaming tradicionales por servidores web que ponen a disposición de los clientes los contenidos de vídeo codificados en varias versiones con distinto nivel de calidad. Cada una de estas versiones o representaciones está dividida en pequeños fragmentos o segmentos que los clientes pueden solicitar mediante el protocolo HTTP. Los clientes pueden solicitar diferentes niveles de calidad en función de los parámetros que consideren más adecuados (ancho de banda de la red, resolución de pantalla, tipo de códec, etc.), lo que les permite adaptarse a condiciones cambiantes del entorno. Como se puede ver, el paradigma DASH ha trasladado el control de la sesión del servidor al cliente y ha sustituido los servidores de streaming por servidores web que simplemente sirven los segmentos de vídeo que los clientes solicitan. Además se esta simplificación de los servidores de streaming, existen otras ventajas asociadas a DASH, como son la utilización de Content Delivery Network (CDN), la compatibilidad con NATs y firewalls, etc. En esta tesis doctoral se lleva a cabo la propuesta de un conjunto de modelos cuyo objetivo es estimar la calidad percibida por los usuarios de los servicios de vídeo basados en DASH. Más concretamente, partiendo de la definición del servicio como un conjunto de componentes de servicio, se desarrollan modelos parciales que estiman la calidad percibida asociada a cada uno de estos componentes: calidad de vídeo, calidad de audio, degradaciones asociadas a la transmisión, etc. Cada una de estas estimaciones de calidad percibida se combinan en un modelo global que estima la calidad percibida total del servicio

Low-complexity high prediction accuracy visual quality metrics and their applications in H.264/AVC encoding mode decision process

In this thesis, we develop a new general framework for computing full reference image quality scores in the discrete wavelet domain using the Haar wavelet. The proposed framework presents an excellent tradeoff between accuracy and complexity. In our framework, quality metrics are categorized as either map-based, which generate a quality (distortion) map to be pooled for the final score, e.g., structural similarity (SSIM), or non map-based, which only give a final score, e.g., Peak signal-to-noise ratio (PSNR). For mapbased metrics, the proposed framework defines a contrast map in the wavelet domain for pooling the quality maps. We also derive a formula to enable the framework to automatically calculate the appropriate level of wavelet decomposition for error-based metrics at a desired viewing distance. To consider the effect of very fine image details in quality assessment, the proposed method defines a multi-level edge map for each image, which comprises only the most informative image subbands. To clarify the application of the framework in computing quality scores, we give some examples showing how the framework can be applied to improve well-known metrics such as SSIM, visual information fidelity (VIF), PSNR, and absolute difference. We compare the complexity of various algorithms obtained by the framework to the Intel IPP-based H.264 baseline profile encoding using C/C++ implementations. We evaluate the overall performance of the proposed metrics, including their prediction accuracy, on two well-known image quality databases and one video quality database. All the simulation results confirm the efficiency of the proposed framework and quality assessment metrics in improving the prediction accuracy and also reduction of the computational complexity. For example, by using the framework, we can compute the VIF at about 5% of the complexity of its original version, but with higher accuracy. In the next step, we study how H.264 coding mode decision can benefit from our developed metrics. We integrate the proposed SSEA metric as the distortion measure inside the H.264 mode decision process. The H.264/AVC JM reference software is used as the implementation and verification platform. We propose a search algorithm to determine the Lagrange multiplier value for each quantization parameter (QP). The search is applied on three different types of video sequences having various motion activity features, and the resulting Lagrange multiplier values are tabulated for each of them. Based on our proposed Framework we propose a new quality metric PSNRA, and use it in this part (mode decision). The simulated rate-distortion (RD) curves show that at the same PSNRA, with the SSEA-based mode decision, the bitrate is reduced about 5% on average compared to the conventional SSE-based approach for the sequences with low and medium motion activities. It is notable that the computational complexity is not increased at all by using the proposed SSEA-based approach instead of the conventional SSE-based method. Therefore, the proposed mode decision algorithm can be used in real-time video coding

Video Content-Based QoE Prediction for HEVC Encoded Videos Delivered over IP Networks

The recently released High Efficiency Video Coding (HEVC) standard, which halves the transmission bandwidth requirement of encoded video for almost the same quality when compared to H.264/AVC, and the availability of increased network bandwidth (e.g. from 2 Mbps for 3G networks to almost 100 Mbps for 4G/LTE) have led to the proliferation of video streaming services. Based on these major innovations, the prevalence and diversity of video application are set to increase over the coming years. However, the popularity and success of current and future video applications will depend on the perceived quality of experience (QoE) of end users. How to measure or predict the QoE of delivered services becomes an important and inevitable task for both service and network providers. Video quality can be measured either subjectively or objectively. Subjective quality measurement is the most reliable method of determining the quality of multimedia applications because of its direct link to users’ experience. However, this approach is time consuming and expensive and hence the need for an objective method that can produce results that are comparable with those of subjective testing. In general, video quality is impacted by impairments caused by the encoder and the transmission network. However, videos encoded and transmitted over an error-prone network have different quality measurements even under the same encoder setting and network quality of service (NQoS). This indicates that, in addition to encoder settings and network impairment, there may be other key parameters that impact video quality. In this project, it is hypothesised that video content type is one of the key parameters that may impact the quality of streamed videos. Based on this assertion, parameters related to video content type are extracted and used to develop a single metric that quantifies the content type of different video sequences. The proposed content type metric is then used together with encoding parameter settings and NQoS to develop content-based video quality models that estimate the quality of different video sequences delivered over IP-based network. This project led to the following main contributions: (1) A new metric for quantifying video content type based on the spatiotemporal features extracted from the encoded bitstream. (2) The development of novel subjective test approach for video streaming services. (3) New content-based video quality prediction models for predicting the QoE of video sequences delivered over IP-based networks. The models have been evaluated using subjective and objective methods

Gradient-based image and video quality assessment

У овој дисертацији разматране су објективне мере процене квалитета слике и видеа са потпуним и делимичним референцирањем на изворни сигнал. За потребе евалуације квалитета развијене су поуздане, рачунски ефикасне мере, засноване на очувању информација о градијенту. Мере су тестиране на великом броју тест слика и видео секвенци, различитих типова и степена деградације. Поред јавно доступних база слика и видео секвенци, за потребе истраживања формиране су и нове базе видео секвенци са преко 300 релевантних тест узорака. Поређењем доступних субјективних и објективних скорова квалитета показано је да је објективна евалуација квалитета веома сложен проблем, али га је могуће решити и доћи до високих перформанси коришћењем предложених мера процене квалитета слике и видеа.U ovoj disertaciji razmatrane su objektivne mere procene kvaliteta slike i videa sa potpunim i delimičnim referenciranjem na izvorni signal. Za potrebe evaluacije kvaliteta razvijene su pouzdane, računski efikasne mere, zasnovane na očuvanju informacija o gradijentu. Mere su testirane na velikom broju test slika i video sekvenci, različitih tipova i stepena degradacije. Pored javno dostupnih baza slika i video sekvenci, za potrebe istraživanja formirane su i nove baze video sekvenci sa preko 300 relevantnih test uzoraka. Poređenjem dostupnih subjektivnih i objektivnih skorova kvaliteta pokazano je da je objektivna evaluacija kvaliteta veoma složen problem, ali ga je moguće rešiti i doći do visokih performansi korišćenjem predloženih mera procene kvaliteta slike i videa.This thesis presents an investigation into objective image and video quality assessment with full and reduced reference on original (source) signal. For quality evaluation purposes, reliable, computational efficient, gradient-based measures are developed. Proposed measures are tested on different image and video datasets, with various types of distorsions and degradation levels. Along with publicly available image and video quality datasets, new video quality datasets are maded, with more than 300 relevant test samples. Through comparison between available subjective and objective quality scores it has been shown that objective quality evaluation is highly complex problem, but it is possible to resolve it and acchieve high performance using proposed quality measures