The evolution of advanced radio transmission technologies for third generation mobile radio systems has paved the way for the delivery of mobile multimedia services. In particular, wireless image and video applications are among the most popular services offered on modern mobile devices to support communication beyond the traditional voice services. The large amount of data necessary to represent the visual content and the scarce bandwidth of the wireless channel impose new challenges for the network operator to deliver high quality image and video services. Link layer metrics have conventionally been used to monitor the received signal quality but were found to not accurately reflect the visual quality as it is perceived by the end-user. These metrics thus need to be replaced by suitable metrics that measure the overall impairments induced during image or video communication and accurately relate them to subjectively perceived quality. In this thesis, we focus on objective metrics that are able to quantify the end-to-end visual quality in wireless image and video communication. Such metrics may then be utilised to support the efficient use of link adaptation and resource management techniques and thus guarantee a certain quality of service to the user. The thesis is divided into four parts. The first part contributes an extensive survey and classification of contemporary image and video quality metrics that may be applicable in a communication context. The second part then discusses the development of the Normalised Hybrid Image Quality Metric (NHIQM) that we propose for prediction of visual quality degradations induced during wireless communication. The metric is based on a set of structural features, which are deployed to quantify artifacts that may occur in a wireless communication system and also are well aligned to characteristics of the human visual system (HVS). In the third part, three metric designs are discussed that utilise the same structural feature set as a basis for quality prediction. Incorporation of further HVS characteristics into the metric design will then improve even more the visual quality prediction performance. The design and validation of all proposed metrics is supported by subjective quality experiments that we conducted in two independent laboratories. Comparison to other state of the art visual quality metrics reveals the ability of the proposed metrics to accurately predict visual quality in a wireless communication system. The last part contributes an application of NHIQM for filter design. In particular, the filtering performance of a de-blocking de-ringing post filter for H.263 video sequences is analysed with regards to visual quality of the filtered sequence when applying appropriate filter parameter combinations.