Lossy compression algorithms

efficient tool for image compression, Wavelet transform gives multiresolution image decomposition. which can .be exploited through vector quantization to achieve high compression ratio. For vector quantization of wavelet coefficients vectors are formed by either coefficients at same level, different location or different level, same location. This paper compares the two methods and shows that because of wavelet properties, vector quantization can still improve compression results by coding only important

1. INTRODUCTION COMPRESSION • What is compression? Data compression is the method of reducing the number of bits to store or transmit the data. It reduces the size of data to save storage space or speed transmission. Cost is aldo decreased for storage and network bandwidth. Compression is performed by a program that uses an algorithm on how to shrink the size of the data. For data transmission, compression can be performed on the data content or on the entire transmission unit.. When information

other words an optimal compression ratio should be chosen so as to suit the needs of medical examination, without compromising with its diagnostic value [2]. 1.2 Types of Compression Image compression can be classified into two types viz. lossless and lossy compression. Lossless compression is the technique of reducing the size of an image without any virtual loss of information. It is also known as reversible form of image compression since the image obtained after compression and then decompression

INTRODUCTION 1.1 What Is Compression Technology ? Compression is representation of data in a compact form. Compression of data, bit rate reduction or source coding involves encoding of data using fewer number of bits. Compression are of two types lossy and lossless. Lossless compression removes such data bits whose removal does not affects the information of the data on the other hand no information losses takes place in lossless compression. Lossy compression reduces bits by finding unnecessary

based compression, its need and importance. Section II presents a brief literature survey on the methods and techniques that were proposed so far for ROI based image compression, their limitation and focus on the importance of this work. 3 Binary Plane Difference Coding This method can be applied in both modes (i) Lossless and (ii) Lossy. The loss less compression technique is based on spatial domain of the image and they are very much suitable for the compression of medical images. The Lossy Binary

Image Compression Using Hybrid SVD-WDR and SVD-ASWDR: A comparative analysis Kanchan Bala (Research Scholar) Computer Science andEngineering Dept. Punjab Technical University Jalandhar, India kanchukashyap@gmail.com Er. Deepinder Kaur (Assistant professor) Computer Science and Engineering Dept. Punjab Technical University Jalandhar, India deepinderkaur.bhullar@gmail.com Abstract---In this paper new image compression techniques are presented by using existing techniques such as Singular value

INTRODUCTION Some people suffer severe motor impairments cannot express their thoughts as healthy for assistance of patients and can be controlled by user alone. It uses EEG signals as input and produces output signals in the form of inverse DWT. Communication system between human brain and computer is called BCI. This enables generation of control signals from brain signals, such as sensory motor rhythms and evoked potentials, therefore persons, because they are not capable

A Wireless Sensor Network can be composed of large number of tiny of sensor nodes spread in a wide area and communicating with each other either directly or through routing mechanisms to the other nodes. One or more of the nodes are the base station with uninterrupted battery source than the other nodes. Since the devices in WSN are often tiny devices with small form factor the computational power of these devices is usually small because there will not support large amount of hardware. Furthermore

2.3. Memory usage The memory usage of image object is a key factor for a program using image files, because normally a Bitmap object expands image data in memory and the size of memory is usually significant as it is directly related to the dimension of the image. 2.3.1. Avoid uncompressing image data However, the first thing worth to discuss is that the Image.FromStream() has a different approach than other means to load an image file into memory, that makes it is possible to not expand the compressed

In today’s world when whole world become digitized there is need not only to store and transmit data but security is also main concern i.e. transmission of data with high security. In earlier time there ware attempts to hide a message in trusted media so as to deliver it across the enemy territory[1]. In the modern time of digital communication, several methods are used for hiding information in any medium. There are many method one of such technique is steganography[2] in which digital images are