Multimedia signals, such as digital images and video sequences, are captured, processed and finally presented to human observers who directly or indirectly judge their quality. During the data acquisition, as well as the many steps of the processing chain, distortions can be introduced in the signal. These distortions may degrade the quality of the content and reduce its acceptability by the end user. The need for methods, which try to quantify and predict users’ opinions upon the quality of multimedia content, is closely related to the need for optimizing the different steps of multimedia production, processing and delivery chain, with the final goal of maximizing user’s satisfaction. These methods consist of algorithms for the automatic prediction of multimedia quality, called ‘objective quality metrics’, or psychophysical experiments to collect data directly from the users, called ‘subjective quality methods’. Overall, both objective and subjective multimedia quality evaluation are still far from being mature research areas. This is due to the fact that multimedia quality perception is multidimensional and many factors may influence user’s satisfaction. This thesis describes the author’s contributions to the research on multimedia quality evaluation, focusing on multimedia processing that involves visual signals. Three topics of interest have been identified: the benchmark and validation of objective quality metrics; the quality assessment for performance evaluation of image and video compression algorithms; the analysis of user-dependent and contextual factors, in order to move from the concept of quality of multimedia signals towards the concept of quality of multimedia experience. For each topic, some open research challenges are identified and addressed. Applications that are of particular interest for service providers, such as video transmission over noisy channels and three-dimensional image and video processing, as well as recent international standardization activities, are considered as study cases.