Transform processing and coding of images Final report

Transform processing and image codin

Complexity adaptation in video encoders for power limited platforms

With the emergence of video services on power limited platforms, it is necessary to consider both performance-centric and constraint-centric signal processing techniques. Traditionally, video applications have a bandwidth or computational resources constraint or both. The recent H.264/AVC video compression standard offers significantly improved efficiency and flexibility compared to previous standards, which leads to less emphasis on bandwidth. However, its high computational complexity is a problem for codecs running on power limited plat- forms. Therefore, a technique that integrates both complexity and bandwidth issues in a single framework should be considered. In this thesis we investigate complexity adaptation of a video coder which focuses on managing computational complexity and provides significant complexity savings when applied to recent standards. It consists of three sub functions specially designed for reducing complexity and a framework for using these sub functions; Variable Block Size (VBS) partitioning, fast motion estimation, skip macroblock detection, and complexity adaptation framework. Firstly, the VBS partitioning algorithm based on the Walsh Hadamard Transform (WHT) is presented. The key idea is to segment regions of an image as edges or flat regions based on the fact that prediction errors are mainly affected by edges. Secondly, a fast motion estimation algorithm called Fast Walsh Boundary Search (FWBS) is presented on the VBS partitioned images. Its results outperform other commonly used fast algorithms. Thirdly, a skip macroblock detection algorithm is proposed for use prior to motion estimation by estimating the Discrete Cosine Transform (DCT) coefficients after quantisation. A new orthogonal transform called the S-transform is presented for predicting Integer DCT coefficients from Walsh Hadamard Transform coefficients. Complexity saving is achieved by deciding which macroblocks need to be processed and which can be skipped without processing. Simulation results show that the proposed algorithm achieves significant complexity savings with a negligible loss in rate-distortion performance. Finally, a complexity adaptation framework which combines all three techniques mentioned above is proposed for maximizing the perceptual quality of coded video on a complexity constrained platform

Shuttle/TDRSS Ku-band downlink study

Assessing the adequacy of the baseline signal design approach, developing performance specifications for the return link hardware, and performing detailed design and parameter optimization tasks was accomplished by completing five specific study tasks. The results of these tasks show that the basic signal structure design is sound and that the goals can be met. Constraints placed on return link hardware by this structure allow reasonable specifications to be written so that no extreme technical risk areas in equipment design are foreseen. A third channel can be added to the PM mode without seriously degrading the other services. The feasibility of using only a PM mode was shown to exist, however, this will require use of some digital TV transmission techniques. Each task and its results are summarized

Orthogonal transform feasibility study

The application of various orthogonal transformations to communication was investigated, with particular emphasis placed on speech and visual signal processing. The fundamentals of the one- and two-dimensional orthogonal transforms and their application to speech and visual signals are treated in detail

Fast Computation of Sliding Discrete Tchebichef Moments and Its Application in Duplicated Regions Detection

International audienceComputational load remains a major concern when processing signals by means of sliding transforms. In this paper, we present an efficient algorithm for the fast computation of one-dimensional and two-dimensional sliding discrete Tchebichef moments. To do so, we first establish the relationships that exist between the Tchebichef moments of two neighboring windows taking advantage of Tchebichef polynomials’ properties. We then propose an original way to fast compute the moments of one window by utilizing the moment values of its previous window. We further theoretically establish the complexity of our fast algorithm and illustrate its interest within the framework of digital forensics and more precisely the detection of duplicated regions in an audio signal or an image. Our algorithm is used to extract local features of such a signal tampering. Experimental results show that its complexity is independent of the window size, validating the theory. They also exhibit that our algorithm is suitable to digital forensics and beyond to any applications based on sliding Tchebichef moments