'Image compression' presentation slideshows

Image compression - PowerPoint PPT Presentation


Scalar Quantization

Scalar Quantization

Scalar Quantization. CAP5015 Fall 2004. Quantization. Definition: Quantization: a process of representing a large – possibly infinite – set of values with a much smaller set. Scalar quantization: a mapping of an input value x into a finite number of output values, y : Q: x ® y

By Ava
(865 views)

Clustering

Clustering

Clustering. CMPUT 466/551 Nilanjan Ray. What is Clustering?. Attach label to each observation or data points in a set You can say this “unsupervised classification” Clustering is alternatively called as “grouping”

By benjamin
(244 views)

Image Compression (Chapter 8)

Image Compression (Chapter 8)

Image Compression (Chapter 8). CS474/674 – Prof. Bebis. Image Compression. The goal of image compression is to reduce the amount of data required to represent a digital image. Image Compression (cont’d). Lossless Information preserving Low compression ratios Lossy

By binah
(193 views)

Image Compression using Vector Quantization

Image Compression using Vector Quantization

Image Compression using Vector Quantization. Nopparat Pantsaena Manas Sangworasil Chinnapat Nantajiwakornchai Tanasak Phanprasit. Research Center for Communication and Information Technology (ReCCIT) King Mongkut’s Institute of Technology Ladkrabang (KMITL) Bangkok, Thailand. Objective.

By jerusha
(425 views)

Image Compression - JPEG

Image Compression - JPEG

Image Compression - JPEG. Video Compression. MPEG Audio compression Lossy / perceptually lossless / lossless 3 layers Models based on speech generation (throat), or ear characterisitics Image compression JPEG based Images take much more memory than voice

By cargan
(244 views)

Steganography In 	Compressed Images

Steganography In Compressed Images

Steganography In Compressed Images. (Advanced Database Systems- Spring 2004). Anurag Sharma,Gautami Shirhatti & Manish Billa. Department of Computer Science, University of Central Florida ,Orlando. ~ Motivation Protection of Digital Media.

By ozzy
(299 views)

Burrows Wheeler Transform In Image Compression

Burrows Wheeler Transform In Image Compression

Burrows Wheeler Transform In Image Compression. Markus G ä rtner David Havelin Classroom Presentation 1st December 2000. Overview. Project Goals Burrows Wheeler Transform (BWT) Application of the BWT: Lossless Compression Lossy Compression Performance Conclusion. Project Goals.

By burke
(216 views)

Image Compression Using Neural Networks

Image Compression Using Neural Networks

Image Compression Using Neural Networks. Vishal Agrawal (Y6541) Nandan Dubey (Y6279). Overview. Introduction to n eural networks Back Propagated (BP) neural network Image compression using BP neural network Comparison with existing image compression techniques. What is a Neural Network?.

By adelie
(480 views)

Image Compression Using Inpainting

Image Compression Using Inpainting

Image Compression Using Inpainting. Min-Wook Jeong Young Min Kim Jungsuk Kwac. Organization. Motivation Structure Inpainting Texture Inpainting Result Conclusion Reference. Motivation. Motivation (Cont.). Structure Inpainting. Recovering general structure (big picture)

By cleatus
(302 views)

Image Compression (Chapter 8)

Image Compression (Chapter 8)

Image Compression (Chapter 8). CSC 446 Lecturer: Nada ALZaben. Outline:. Introduction. Image Compression Model. Compression Types . Data Redundancy. Redundancy Types. Coding redundancy Lossless compression. Introduction.

By lotus
(204 views)

CS 414 – Multimedia Systems Design Lecture 7 – Basics of Compression (Part 2)

CS 414 – Multimedia Systems Design Lecture 7 – Basics of Compression (Part 2)

CS 414 – Multimedia Systems Design Lecture 7 – Basics of Compression (Part 2). Klara Nahrstedt Spring 2009. Administrative . MP1 is posted . Huffman Encoding . Statistical encoding To determine Huffman code, it is useful to construct a binary tree Leaves are characters to be encoded

By mireille
(152 views)

SIMS-201

SIMS-201

SIMS-201. Audio Digitization. Overview. Chapter 12 Digital Audio Digitization of Audio Samples Quantization Reconstruction Quantization error. Digitization of Audio Samples. Audio signals are continuous in time and amplitude

By zinnia
(116 views)

ECE472/572 - Lecture 12

ECE472/572 - Lecture 12

ECE472/572 - Lecture 12 . Image Compression – Lossy Compression Techniques 11/10/11. Fidelity criteria to measure performance. Data 3. Lossy. Information. Data 2. Lossless. Data 1. Measure information. Data redundancy. Data compression. Compression Approaches.

By holiday
(198 views)

Wavelets in Image Compression

Wavelets in Image Compression

Wavelets in Image Compression. Bhushan D Patil PhD Research Scholar Department of Electrical Engineering Indian Institute of Technology, Bombay Powai, Mumbai 40076. What are the principles behind compression?.

By darci
(222 views)

Run Length Encoder/Decoder

Run Length Encoder/Decoder

Run Length Encoder/Decoder. EE113D Project Authors: Imran Hoque Yipeng Li Diwei Zhang. Introduction – What is RLE?. Compression technique Represents data using value and run length Run length defined as number of consecutive equal values e.g

By aram
(140 views)

Lossy Compression

Lossy Compression

Lossy Compression. William Dayton Nick Trojanowski. Lossy file compression compresses files by trimming out data, and therefore quality, from the original data. The loss of data is not usually enough to be noticeable by the user, but can immensely save on file size. Definition.

By genero
(158 views)

Flickr and Digital Photography

Flickr and Digital Photography

Flickr and Digital Photography. Flickr in a Nutshell. Community of photographers Millions of users Special Interest Groups Sharing Images Creative Commons. Features. Hosting Photostream RSS feed Editing ( picnik ) Rotate, crop, resize, exposure, colors, sharpen, red-eye Tags

By liona
(70 views)

Introduction

Introduction

Introduction. CSc I6716 Spring 2011 3D Computer Vision . Instructor: Zhigang Zhu City College of New York zzhu@ccny.cuny.edu. Introduction. Course Information. Basic Information: Course participation Books, notes, etc. Web page – check often! Homework, Assignment, Exam

By althea
(69 views)

Seminar Announcement

Seminar Announcement

Seminar Announcement. You are invited to a talk on Image Compression by Dr. C. Wayne Brown Faculty of Information Technology Multimedia University (Cyberjaya Campus) Venue : BR1022 (FIT, Cyberjaya) Date : 23-Feb-2001 (Friday) Time : 10:30 am-12:00 noon.

By jesse
(147 views)

CS 315 Data Structures Fall 2011 Instructor: B. (Ravi) Ravikumar Office: 116 I Darwin Hall Phone: 664 3335 E-

CS 315 Data Structures Fall 2011 Instructor: B. (Ravi) Ravikumar Office: 116 I Darwin Hall Phone: 664 3335 E-

CS 315 Data Structures Fall 2011 Instructor: B. (Ravi) Ravikumar Office: 116 I Darwin Hall Phone: 664 3335 E-mail: cs315spring11@gmail.com Course Web site: http://ravi.cs.sonoma.edu/cs315fa11. Textbook:. Data Structures and Algorithm Analysis in C++. 3 rd edition

By hollye
(144 views)

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