As i hav find 
there are a lot of computer professional gupies and Gupans ,I just need technical help from them for my project.The little intro of the project is given below.My Aim is to write **IEEE paper as well ** ,As this is research oriented project.This can easily be done.I just required help if u hav done somthing in DIP (compression technique),or you hav got som E-Book ,you can shared that,if you hav some Knowledge abt current research work regarding this topic ,or You hav som suggestion, whatever u have shared that with me.You better read the Project summary, this is just the outline hmm,
Title: Image Compression and denoising Techniques
PROJECT SUMMARY
Abstract:
The main emphasis of this project is on study of different image compression techniques and implementation of Wavelet technique (the discrete wavelet transform) using JPEG2000 as this is the technique using discrete wavelet transform. The DWT provides powerful insight into an image’s spatial and frequency attributes. Image processing is important for many applications in a wide range of areas such as medicine, defense, computer Graphics and astronomy. One problem arising in all of these areas is the need to smooth and denoise images. Many existing techniques for image denoising can be expressed in terms of minimizing a particular cost function. Image denoising still remains a challenge for Researchers because noise removal introduces artifacts and causes blurring of the images. There are two basic approaches to image denoising, spatial filtering methods and transform domain filtering methods. In spatial, linear and non linear filters are used for denoising the image. In transform domain we used data and non data adaptive transform. In non data adaptive transform, wavelet domain is used. These are the classification of image denosising methods.
Application:
The method used in compression techniques in general is to allow an image to be encoded into a smaller size and then decoded into the original format. The common compression methods are Run-Length Encoding (RLE) and Lempel/Ziv coding (LZW). The main principle behind reducing the size of the image is coding redundancy. Coding redundancy is based upon the idea that in an image there are some colors that are used frequently and other that are used infrequently. If there are repeated colors this soon would cause “repetition” and therefore a certain amount of redundancy would appear within the system. In a distributed environment large image files remain a major bottleneck within systems. Compression is an important component of the solutions available for creating file sizes of manageable and transmittable dimensions. Increasing the bandwidth is another method, but the cost sometimes makes this a less attractive solution. Platform portability and performance are important in the selection of the compression/decompression technique to be employed. The easiest way to reduce the size of the image file is to reduce the size of the image itself. By shrinking the size of the image, fewer pixels need to be stored and consequently the file will take less time to load. The problem with this is that if an image file is reduced the quality of the image is reduced. Clearly there is a problem if every image you wished to send had to be reduced in quality. Thus two types of image compression exists “Lossless” and “Lossy” compression. Currently Digital Video Interface (DVI), Joint Photographic Experts Group (JPEG), and Motion Pictures Experts Group (JPEG) are the three compression techniques that are widely used. In general, lossy techniques provide far greater compression ratios than lossless techniques. There are different Lossless Coding techniques that will be included in studies are Run Length Encoding, Huffman Encoding, Area Coding, Lossy Coding Technique, Transform Coding (DCT/Wavelets/Gabor), Segmented Image Coding. In this project we will implement wavlet (JPEG-2000: Image Compression Standard technique).
Introduction:
Digital image compression is now essential. The Internet has resulted in a network by which almost any form of communication is possible. The average net user communicated through text, images and video, of these the simplest and easiest is through text as it is quick as simple to use as sending text very little bandwidth. The problem with images and videos is that they require a large amount of bandwidth to send and receive. Therefore there is a need to decrease the size of the image or video sent or received. The aim of data compression techniques is to reduce the amount of data needed to accurately represent an image, such that this image can be economically transmitted or archived.
Objectives:
Survey of different compression techniques.
Implementation of Wavelet (JPEG-2000): Image Compression Standard Technique.
Complete Study and understanding of different image compression techniques.
Areas of improvement:
Reduction of size of the image
Suggest The Best and efficient Compression techniques
I will be highly grateful and ur efforts regarding this project will be appreciated:)
You can mail me at my email address as well
[EMAIL=“[email protected]”][email protected]
u r sweeeeeeeet and cute too:hehe: