The protection of digital images and video from unauthorized access is important for a number of applications, including privacy protection in video surveillance and digital rights management for consumer applications. However, traditional cryptographic methods are not well suited to digital visual content. Applying standard encryption approaches to the entire content can require significant computational resources due to the large size of the data. Furthermore, digital images and video often need to be manipulated,such as by resizing or transcoding, which traditional encryption would hinder. A number of image and video-specific encryption approaches have been proposed in the literature, but many of the them have significant negative impact on the ability to compress the data, which is a necessary requirement of most imaging systems. In this work, a secure image coder, called Secure Set Partitioning in Hierarchical Trees (SecSPIHT), is proposed. It combines wavelet-based image coding (compression) with efficient encryption. The encryption is applied to a small number of selected bits in the code domain, to achieve complete confidentiality of all the content while having no negative impact on compression performance. The output of the system is a secure code that cannot be decrypted and decoded without the provision of a secret key. It has superior rate-distortion performance compared to JPEG and JPEG2000, and the bit-rate can be easily scaled via a simple truncation operation. The computational overhead of the encryption operation is very low, typically requiring less than 1% of the coded image data to be encrypted. A related secure object-based coding approach is also presented. Called Secure Shape and Texture Set Partitioning in Hierarchical Trees (SecST-SPIHT), it codes and encrypts arbitrarily-shaped visual objects. A privacy protection system for video surveillance is proposed, using SecST-SPIHT to protect private data, such as face and body images appearing in surveillance footage. During normal operation of the system, the private data objects are protected via SecST-SPIHT. If an incident occurs that requires access to the data (e.g., for investigation), a designated authority must release the key. This is superior to other methods of privacy protection which irreversibly blur or mask the private data.

Fourth Generation (4G) cellular technology Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) offers high data rate capabilities to mobile users; and, operators are trying to deliver a true mobile broadband experience over LTE networks. Mobile TV and Video on Demand (VoD) are expected to be the main revenue generators in the near future [36] and efficient video streaming over wireless is the key to enabling this. 3GPP recommends the use of H.264 baseline profiles for all video based services in Third Generation (3G) Universal Mobile Telecommunication System (UMTS) networks. However, LTE networks need to support mobile devices with different display resolution requirements like small resolution mobile phones and high resolution laptops. Scalable Video Coding (SVC) is required to achieve this goal. Feasibility study of SVC for LTE is one of the main agenda of 3GPP Release10. SVC enhances H.264 with a set of new profiles and encoding tools that may be used to produce scalable bit streams. Efficient adaptation methods for SVC video transmission over LTE networks are proposed in this thesis. Advantages of SVC over H.264 are analyzed using real time use cases of mobile video streaming. Further, we study the cross layer adaptation and scheduling schemes for delivering SVC video streams most efficiently to the users in LTE networks in unicast and multicast transmissions. We propose SVC based video streaming scheme for unicast and multicast transmissions in the downlink direction, with dynamic adaptations and a scheduling scheme based on channel quality information from users. Simulation results indicate improved video quality for more number of users in the coverage area and efficient spectrum usage with the proposed methods.

Recent algorithms for video coding achieve a high-quality transmission at moderate bit rates. On the other hand, those coders are very sensitive to transmission errors. Many research projects focus on methods to conceal such errors in the decoded video sequence. Motion compensated prediction is commonly used in video coding to achieve a high compression ratio. This thesis proposes an algorithm which uses the motion compensated prediction of a given video coder to predict a sequence of several complete frames, based on the last correctly decoded images, during a transmission interruption. The proposed algorithm is evaluated on a video coder which uses a dense motion field for motion compensation. A drawback of predicting lost fields is the perceived discontinuity when the decoder switches back from the prediction to a normal mode of operation. Various approaches to reduce this discontinuity are investigated.

In this Master Thesis, a model of a video coding system that uses the transportation plan taken from the calculation of the Kantorovich distance is developed. The coder uses the transportation plan instead of the differential image and sends it through blocks of transformation, quantization and coding. The Kantorovich distance is a rather unknown distance metric that is used in optimization theory but is also applicable on images. It can be defined as the cheapest way to transport the mass of one image into another and the cost is determined by the distance function chosen to measure distance between pixels. The transportation plan is a set of finitely many five-dimensional vectors that show exactly how the mass should be moved from the transmitting pixel to the receiving pixel in order to achieve the Kantorovich distance between the images. A vector in the transportation plan is called an arc. The original transportation plan was transformed into a new set of four-dimensional vectors called the modified difference plan. This set replaces the transmitting pixel and the receiving pixel with the distance from the transmitting pixel of the last arc and the relative distance between the receiving pixel and the transmitting pixel. The arcs where the receiving pixels are the same as the transmitting pixels are redundant and were removed. The coder completed an eleven frame sequence of size 128x128 pixels in eight to ten hours.

In this thesis, we study the concept of scalable video coding as implemented in the extension to the H.264 video coding standard. Specifically, for the spatial and quality scalability scenarios, we propose an optimization algorithm based on the Soft Decision Quantization (SDQ) concept, which aims at jointly optimizing all layers being encoded. The performance of the algorithm was assessed in an SVC implementation. Experimental results show, that the proposed method significantly improves the coding efficiency when compared to an unmodified SVC encoder.

Video compression is an essential component of present-day applications and a decisive factor between the success or failure of a business model. There is an ever increasing demand to transmit larger number of superior-quality video channels into the available transmission bandwidth. Consumers are increasingly discerning about the quality and performance of video-based products and there is therefore a strong incentive for continuous improvement in video coding technology for companies to have market edge over its competitors. Even though processor speeds and network bandwidths continue to increase, a better video compression results in a more competitive product. This drive to improve video compression technology has led to a revolution in the last decade. In this thesis we addresses some of these data compression problems in a practical multimedia system that employ Hybrid video coding schemes. Typically Real life video signals show non-stationary statistical behavior. The statistics of these signals largely depend on the video content and the acquisition process. Hybrid video coding schemes like H264/AVC exploits some of the non-stationary characteristics but certainly not all of it. Moreover, higher order statistical dependencies on a syntax element level are mostly neglected in existing video coding schemes. Designing a video coding scheme for a video coder by taking into consideration these typically observed statistical properties, however, offers room for significant improvements in coding efficiency.In this thesis work a new frequency domain curve-fitting compression framework is proposed as an extension to H264 Context Adaptive Binary Arithmetic Coder (CABAC) that achieves better compression efficiency at reduced complexity. The proposed Curve-Fitting extension to H264 CABAC, henceforth called as CF-CABAC, is modularly designed to conveniently fit into existing block based H264 Hybrid video Entropy coding algorithms. Traditionally there have been many proposals in the literature to fuse surfaces/curve fitting with Block-based, Region based, Training-based (VQ, fractals) compression algorithms primarily to exploiting pixel- domain redundancies. Though the compression efficiency of these are expectantly better than DCT transform based compression, but their main drawback is the high computational demand which make the former techniques non-competitive for real-time applications over the latter. The curve fitting techniques proposed so far have been on the pixel domain. The video characteristic on the pixel domain are highly non-stationary making curve fitting techniques not very efficient in terms of video quality, compression ratio and complexity. In this thesis, we explore using curve fitting techniques to Quantized frequency domain coefficients. we fuse this powerful technique to H264 CABAC Entropy coding. Based on some predictable characteristics of Quantized DCT coefficients, a computationally in-expensive curve fitting technique is explored that fits into the existing H264 CABAC framework. Also Due to the lossy nature of video compression and the strong demand for bandwidth and computation resources in a multimedia system, one of the key design issues for video coding is to optimize trade-off among quality (distortion) vs compression (rate) vs complexity. This thesis also briefly studies the existing rate distortion (RD) optimization approaches proposed to video coding for exploring the best RD performance of a video codec. Further, we propose a graph based algorithm for Rate-distortion. optimization of quantized coefficient indices for the proposed CF-CABAC entropy coding.

One of the major applications driving wireless network services is video streaming, which is based on the ability to simultaneously multicast the same video contents to a group of users, thus reducing the bandwidth consumption. On the other hand, due to slow progress in battery technology, the investigation of power saving technologies becomes important. IEEE 802.16e (also known as Mobile WiMAX) is currently the international MAC (medium access control) standard for wireless metropolitan area networks. However, in 802.16e, the power saving class for multicast traffic is designed only for best-effort-based management operations. On the other hand, SMBC-AMC adopts the concepts of ¡§multicast superframe¡¨ and ¡§logical broadcast channel¡¨ to support push-based multicast applications. However, SMBC-AMC requires that (1) the number of frames in each logical broadcast channel must be equal, (2) all mobile stations must have the same duty cycle, and (3) the base station must use the same modulation to send data in a frame. These imply that SMBC-AMC is too inflexible to reach high multicast energy throughput. In this thesis, we propose cross-layer energy efficient multicast scheduling algorithms, called EEMS-AMC, for scalable video streaming. The goal of EEMS-AMC is to find a multicast data scheduling such that the multicast energy throughput of a WiMAX network is maximum. Specifically, EEMS-AMC has the following attractive features: (1) By means of admission control and the restriction of the multicast superframe length, EEMS-AMC ensures that the base layer data of all admitted video streams can be delivered to mobile stations in timeliness requirements. (2) EEMS-AMC adopts the greedy approach to schedule the base layer data such that the average duty cycle of all admitted stations can approach to the theoretical minimum. (3) EEMS-AMC uses the metric ¡§potential multicast throughput¡¨ to find the proper modulation for each enhancement layer data and uses the metric ¡§multicast energy throughput gain¡¨ to find the near-optimal enhancement layer data scheduling. Simulation results show that EEMS-AMC significantly outperforms SMBC-AMC in terms of average duty cycle, multicast energy throughput, multicast packet loss rate, and normalized total utility.

A novel residual prediction algorithm is proposed for high-bit-rate video coding in this work. We analysis the relationship between the residual data and different quantization parameters, according to the comparison results, we observe that the residual data is raised rapidly when the quality increases. Consequently, in order to reduce the bitrate, we propose a new residual prediction algorithm, it mainly reduce the residual data when the quantization parameter is finer. The proposed algorithm not only reduces the bitrate but also improves the video quality for high-bit-rate coding. Experimental results show that the proposed algorithm outperforms H.264/AVC. Compared to H.264/AVC, the proposed method decreases about 9.66% bitrate in average. The experimental results demonstrated that the second-order-residual prediction algorithm is efficiency for high-bit-rate coding.

This thesis proposes resource allocation algorithms for multi-input multi-output (MIMO) relay and Scalable H.264/AVC video transmission over cooperative communication networks. For MIMO relay, we explore the reception diversity with maximal ratio combining (MRC) and transmission diversity with space-time block codes (STBC) respectively. Then, a condition is proposed to maximize the overall output signal-to-noise ratio (SNR). In this condition, the ineffective relays will be excluded in sequence from the cooperation. Simulation results indicate that the effect of bit error rate (BER) through the relay selection is similar to the scheme which applies all relays, but the amounts of used relay decreased. For Scalable H.264/AVC video, by introducing frame significance analysis, the video quality dependency between coding frame and its references is investigated for temporal layers and quality layers. The proposed algorithm allocates the relay and sub-band to each layer based on channel conditions and the priority of classified video packets. Experimental results indicate that the proposed algorithm is superior to the temporal-based allocation and quality-based allocation cooperative schemes.

In this thesis, we proposed the series methods of moving object segmentation and object application. These methods are the moving object segmentation method in wavelet domain, double change detection method, global motion estimation method, and the moving object segmentation in the motion background. First, we proposed the Video Object Segmentation Method in Wavelet Domain. We use the Change Detection Method with the different thresholds in four wavelet sub-bands. The experiment results show that we obtain further object shape information and more accurately extracting the moving object. In the double change detection method, we proposed the method for moving object segmentation using three successive frames. We use change detection method twice in wavelet domain. After applying the Intersect Operation, we obtain the accurately moving object edge map and further object shape information. Besides, we proposed the global motion estimation method in motion scene. We propose a novel global motion estimation using cross point for the reconstruction of background scene in video sequences. Due to the robust character and limit number of cross points, we can get the Affine parameters of global motion in video sequences efficiency. At last, we proposed the object segmentation method in motion scene. We use the motion estimation method to estimate the global motion between the consecutive frames. We reconstruct a wide scene background without moving objects by the consecutive frames. At last, the moving objects will be segmented easily by comparing the object frame and the relative part in wide scene background. The Results of our proposed have good performance in the different type of video sequences. Hence, the methods of our thesis contribute to the video coding in Mpeg-4 and multimedia technology.