PPT-Parallel Image Processing

Mohammadhossein Behgam Agenda Need for parallelism Challenges Image processing algorithms Data handling amp Load Balancing Communication cost amp performance What is the problem Image Processing applications can be very computationally demanding due to. Pattern Recognition Vol. 5 , No. 4 , Decem ber , 2012 31 Image Zooming and Multiplexing Technique s based on K - Space Transformation A. Ammar, E.M. Saad, I. Ashour and M. El zorkany National Te CUDA Lecture 1. Introduction to Massively Parallel Computing. A quiet revolution and potential buildup. Computation: TFLOPs . vs. . 100 GFLOPs. CPU in every PC – massive volume and potential impact. Dr. Guy Tel-. Zur. Lecture 10. Agenda. Administration. Final presentations. Demos. Theory. Next week plan. Home assignment #4 (last). Final Projects. Next Sunday: Groups 1-1. 6. will present. Next Monday: Groups 1. Processing & Machine Vision. By:. Dr. Rajeev Srivastava. Associate Professor, CSE, IIT(BHU), Varanasi. Fundamentals of . Digital Image Processing. • Applications of image processing. • What's an image?. Thomas Sangild Sørensen. Course overview. Department of Computer Science. Introduction . to computer graphics and image processing (Q1). Data-parallel computing (Q1). Advanced image processing (Q2). Anthony Waterman. Topics to Discuss. Are online games . c. onceptually. . p. arallel?. What portions of a game benefit from parallelization?. Graphics Processing Units (GPUs) . General-Purpose . C. omputing . Pumice Depth Below . Water . as a Function of Time. Behnaz. Hosseini. Havre, MESH . and Pumice Experiments. P. umice deposits from 2012 . Kermadec. Islands submarine eruption north of New Zealand. Havre caldera samples collected by MESH team using remotely operated vehicle Jason. 1. Image. Rich info. from visual data. Examples of images around us. natural photographic images; . . artistic and engineering drawings. scientific images (satellite, medical, etc.). “Motion pictures” => video. Madan Musuvathi. . Visiting Professor, UCLA . Principal Researcher, Microsoft Research. Mid-point feedback. Are you learning from the papers we are reading?. Do you find class discussions helpful?. Does preparing for the class presentation help? . Pipelining. Instruction Pipeline. Pipeline Hazards and their solution. Array and Vector Processing. Pipelining and Vector Processing. Parallel Processing. It refers to techniques that are used to provide simultaneous data processing.. Divya Spandana . Marneni. Agenda. What is Big Data. Big Data and image processing. Why to analyze big images. Complexity involved in processing. Hadoop Image processing framework. Image Retrieval in big data. COBE for BIG KIDSDiscovering how the results of the COSMIC BACKGROUND EXPLORER SATELLITE help us understand the early UNIVERSE Jatila van der Veen REMOTE ACCESS ASTRONOMY PROJECT PHYSICS DEPARTM 1 INTRODUCTIONImage processing is the frequently used technique in vast areas like medical image astronomical data analysisand so on The collection of images is increased to petabytes in last few Recognition Vol.7, No. 2 (2014), pp. 3 89 - 3 9 8 http://dx.d oi.org/10.14257/ijsip.2014.7. 2 . 3 6 ISSN: 2005 - 4254 IJSIP Copyright ⓒ 201 4 SERSC Extraction of Optic Cup in Retinal Fundus image