PPT-Digital Image Compression Using Bit Plane Slicing Method

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. Smash the information to bits. Overview. The primary goal of image compression is to minimize the memory footprint of image data so that storage and transmission times are minimized. . Storage capacity can be limited, as is the case with digital cameras. Processing and Exporting Images. Ivan . Zhekov. Telerik Web Design Course. html5course.telerik.com. . Front-end Developer. http://joneff.info. . Table of Contents. Adobe . Photoshop. Photoshop Toolboxes. Lecture 9: Video, TV & Film. Georgia Gwinnett College. School of Science and Technology. Dr. Jim Rowan. In the next several lectures…. Film & TV & Video & Animation. Issues that arise from conversion. 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). 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. Image compression. Introduction. Image Compression: It is the Art & Science of reducing the amount of data required to represent an image.. It is the most useful and commercially successful technologies in the field of Digital Image Processing.. Vinay Raj Hampapur. Wendy Ni. Stanford University. March 8, 2011. Outline. Motivation. Description of our method. Results and comparisons. Achievements. Future work. Acknowledgement. References. 2. EE398A: Direction-Adaptive KLT for Image Compression. D. Clunie. of the IAEA publication (. ISBN 978-92-0-131010-1):. Diagnostic . Radiology Physics: . A Handbook for Teachers and Students. . . Objective:. . . To familiarize the student with terminology and practical issues associated with digital imaging.. On the Noise Level Estimation. INTERIM. . PRESENTATION. SPRING 2015. ADVISOR: Dr. . K.R.Rao. Presented by, . . . Komandla. . Sai. . Venkat. ,. UTA id: 1001115386. Cengage. Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.. Lessons. Digital Media, 3e. 2. Lesson 3.1: . Distinguishing . (How to use the various settings on your digital camera). Image Size. Image Size. Large, medium, small, etc.. Choose whatever the largest image size gives you. the most flexibility (enlarging, cropping, high-quality printing, etc.). Srivastav. PROBLEM. Image require a lots of space as file & 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 & transmission time.. Class Rules and Responsibilities. What will be learning?. . 106-Static and Dynamic Visualization. . 105-Synthesize Data for . SciVis. Video-Real Life applications. 6.01: Recognize Digital Image Format. is a . lossy compression. method used to . compress images. using . fractals. . The method is best suited for photographs of natural scenes (. trees. , . mountains. , . ferns. , . clouds. ). The fractal compression technique relies on the fact that in certain images, parts of the image resemble other parts of the same image..