DCT IMAGE COMPRESSION

ABSTRACT The rapid growth of digital imaging applications, including desktop publishing, multimedia, teleconferencing, and high definition television (HDTV) has increased the need for effective and standardized image compression techniques. Among the emerging standards are JPEG, for compression of still images ; MPEG, for compression of motion video and CCITT H.261 (also known as Px64), for compression of video telephony and teleconferencing. All three of these standards employ a basic technique known as the discrete cosine transform (DCT)

INTRODUCTION The discrete cosine transform (DCT) is a technique for converting a signal into elementary frequency components. It is widely used in image compression. Here we develop some simple functions to compute the DCT and to compress images. These functions illustrate the power of Mathematical in the prototyping of image processing algorithms.

What is dct Dct has emerged as the image transformation in most visual system Dct has been widely deployed by modern video using standards for example MPEG,JVT etc. DCT is useful in processing one- dimensional signals such as speech waveforms.

IMAGE COMPRESSION  Image compression is very important for efficient transmission and storage of images . Demand for communication of multimedia data through the telecommunications network and accessing the multimedia data through Internet is growing explosively. With the use of digital cameras, requirements for storage, manipulation, and transfer of digital images, has grown explosively . These image files can be very large and can occupy a lot of memory

NEED OF COMPRESSION The need for image compression becomes apparent when number of bits per image are computed resulting from typical sampling rates and quantization methods. . For example, the amount of storage required for given images is (i) a low resolution, TV quality, color video image which has 512 x 512 pixels/color,8 bits/pixel, and 3 colors approximately consists of 6 x 10⁶ bits;

PRINCIPLE BEHIND COMPRESSION Number of bits required to represent the information in an image can be minimized by removing the redundancy present in it Image compression research aims to reduce the number of bits required to represent an image by removing the spatial and spectral redundancies as much as possible.

HOW IMAGES ARE FORMED Digital photography : It uses an array of electronic photo –detector to capture the image focused by the lens as opposed to an exposure on photographic film .

CONTD.. Raw image format – A camera raw image file contains minimally processed data from the image sensor of a digital camera , image scanner or motion picture film scanner .

ADVANTAGE It has been implemented in single integrated circuit; It has the ability to pack most information in fewest coefficients; It minimizes the block like appearance called blocking artifact that results when boundaries between sub-images become visible.

CONCLUSION DCT is used for transformation in JPEG standard. DCT performs efficiently at medium bit rates. This project successfully implemented the DCT for image compression .

FUTURE SCOPE In near future we will extend this work by integrating the 2DCT based compression with run length coding to reduce the size of digital images in efficient manner. However in the discussed work the compression levels are selected manually in near future we will try to find the way in which compression factor can be selected automatically