Image compression
Loading...
Date
2003
Journal Title
Journal ISSN
Volume Title
Publisher
UMT.Lahore
Abstract
An enormous amount of data is produced when a 2-D light intensity function is sampled and quantized to create a digital image. In fact the amount of data generated may be so great that it results in impractical storage, processing, and communications requirements. For instance more than 25 gigabytes (25 x 1 (Mbytes) of data are required to represent the Encyclopedia Britannica in digital form. Image compression addresses the problem of reducing the amount of data required to represent a digital image. The underlying basis of the reduction process is the removal of redundant data from a mathematical viewpoint, this amount to transforming a 2-D pixel array into a statistically uncorrelated data set. The transformation is applied prior to storage or transmission of the image. At some later time the compressed image is decompressed to reconstruct the original image or an approximation to it. Over the years, the need for image compression has grown steadily. Currently, it is recognized as an "enabling technology." For example, image compression has been and continues to be cmcial to the growth of multimedia computing (that is, the use of digital computers in printing and publishing and video production and dissemination). In addition, it is the natural technology for handling the increased spatial resolutions of today's imaging sensors and evolving broadcast television standards. Furthermore, image compression plays a crucial role in many important and diverse applications, including televideo-conferencing, remote sensing (the use of satellite imagery for weather and other earth-resource applications), document and medical imaging, facsimile transmission (FAX), and the control of remotely piloted vehicles in military, space, and hazardous waste control applications. In short, an ever-expanding number of applications depend on the efficient manipulation, storage, and transmission of binary, gray-scale, or color images. We will first examine both the theoretic and practical aspects of the image compression process. There are different standards and groups working in image processing field for example JPEG.Basic steps performed on an image during image compression are:
1. Transform image to luminance/chrominance color space(YCbCr).
2. Reduce the color components (optional).
3. Partition image into 8*8 pixel blocks and perform the DCT on each block.
4. Quantize resulting DCT coefficients.
5. Entropy codes the reduced coefficients.