Faculty Publications
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Item This letter presents techniques for improving the distribution of the number of stack entries, for stack sequential decoding over hard quantized channel, with emphasis on high rate codes. It is shown that, for a class of high rate b/(b+1) codes, a table-based true high rate approach can be easily implemented for obtaining decoding advantage over the punctured approach. Modified algorithms, which significantly improve the distribution of the number of stack entries and decoding time, are proposed for rate 1/N codes and high rate b/(b+1) codes.(IEEE, On low complexity stack decoding of convolutional codes) D'Souza, J.; Maskara, S.L.1999Item Super-resolution video generation algorithm for surveillance applications(Maney Publishing Suite 1C, Joseph's Well, Hanover Walk Leeds LS3 1AB, 2014) Pais, A.R.; D'Souza, J.; Reddy, R.M.Video surveillance is one of the major applications where high-resolution (HR) images are crucial. Since the video camera has limited spatial and temporal resolution, there is a need for super resolution video generation algorithms. In this paper, we have presented a novel technique for activity detection in the surveillance video. To achieve this goal, we have proposed and investigated efficient algorithms for Video Object Plane (VOP) generation, shadow removal from VOP and super-resolved VOP generation, for activity detection from surveillance video. The proposed VOP generation algorithm is computationally efficient and works for both dynamic and static backgrounds. The novel shadow removal algorithm for the VOP is based on texture and its performance has been studied based on average shadow detection and discrimination rates. The proposed super-resolution video generation algorithm has been designed using edge models. The performance of this algorithm has been evaluated using a numerical analysis technique and is found to be better than bi-cubic and bi-linear interpolation techniques. © 2014 RPS.