PPT-IMAGE COMPRESSION BY:Dr . Rajeev

Srivastav PROBLEM Image require a lots of space as file amp can be very large They need to be exchange from various imaging system There is a need to reduce both the amount of storage Space amp transmission time. By Cabel Sholdt and Paul Zeman. Overview. Why Fractal Image Compression. Mathematical Background. How does it work?. Examples. Possible Improvements. Why Fractal Image Compression. Different type of compression scheme worth exploring. Demijan. . Klinc. * . Carmit. . Hazay. † . Ashish. . Jagmohan. **. Hugo . Krawczyk. ** . Tal Rabin. **. * . Georgia . Institute of . Technology. ** . IBM T.J. Watson Research . Labs. † . Introduction. Compression is the reduction in size of data in order to save space or transmission time. . Compression is the process of reducing the size of a file by encoding its data information more efficiently . Petter Svärd, . Benoit . Hudzia. , Johan Tordsson and Erik Elmroth. Umeå University, . Dept. . of. . Computing. Science. VEE 2011, Newport Beach, CA, USA. Live migration. “Transfer . a VM from one host to . Jinseok. Choi and Brian L. Evans. Wireless Networking & Communication Group. The University of Texas as . Austin. Collaboration with Robert . W. Heath, Jr. , . and . Jeonghun. Park. 1. 2. Traditional Radio Access Network. at 75 Gb/s on a GPU. Molly A. O’Neil and Martin Burtscher. Department of Computer Science. Introduction. Scientific simulations on HPC clusters. Run on interconnected compute nodes. P. roduce . and transfer lots of . Shuochao Yao, Yiwen Xu, Daniel Calzada. Network Compression and Speedup. 1. Source: . http://isca2016.eecs.umich.edu/. wp. -content/uploads/2016/07/4A-1.pdf. Network Compression and Speedup. 2. Why smaller models?. Póth Miklós. Fürstner Igor. Subotica Tech. Data. compression. Lossless - all original data can be recovered when the file is uncompressed. The signal is perfectly reconstructed from the available samples. (ZIP, GIF, PNG). Póth Miklós. Fürstner Igor. Subotica Tech. Data. compression. Lossless - all original data can be recovered when the file is uncompressed. The signal is perfectly reconstructed from the available samples. (ZIP, GIF, PNG). On the Noise Level Estimation. INTERIM. . PRESENTATION. SPRING 2015. ADVISOR: Dr. . K.R.Rao. Presented by, . . . Komandla. . Sai. . Venkat. ,. UTA id: 1001115386. Saliency and KAZE Features Authors: Siddharth Srivastava, Prerana Mukherjee, Dr. Brejesh Lall SPCOM 2016 Department of Electrical Engineering Indian Institute of Technology, Delhi Overview • Intro Gennady Pekhimenko. § . Vivek Seshadri. §. Onur Mutlu. . §. . Michael A. Kozuch. †. Phillip B. Gibbons. † . Todd C. Mowry. . §. § . Carnegie Mellon University . † . Intel Labs Pittsburgh. 1. Image Compression . Image compression involves reducing the size of image data file, while is retaining necessary information, the reduced file is called the compressed file and is used to reconstruct the image, resulting in the decompressed image. The original image, before any compression is performed, is called the uncompressed image file. The ratio of the original, uncompressed image file and the compressed file is referred to as the . Topics: . Diffy. , Morph, Gradient Compression. 3D CNNs. Used for video processing. Examining a series of F images in one step. T is typically 3. Note that F reduces as we advance (also because of pooling).