Literature Survey on Color Image Compression

The need for an efficient technique for compression of Images ever increasing because the raw images need large amounts of disk space seems to be a big disadvantage during transmission & storage. Even though there are so many compression technique which is faster, memory efficient and simple surely suits the requirements of the user. This paper consists of review of some of the color image compression techniques. I. Introduction It is used specially for the compression of images where tolerable degradation is required. With the wide use of computers and consequently need for large-scale storage and transmission of data, efficient ways of storing of data have become necessary. With the growth of technology and entrance into the Digital Age, the world has found itself among a vast amount of information. Dealing with such huge information can often present difficulties. Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level. The reduction in file size allows more images to be stored in a given amount of disk or memory space. It also reduces the time required for images to be sent over the Internet or downloaded from Web pages. JPEG and JPEG 2000 are two important techniques used for image compression. JPEG, image compression standard use DCT (DISCRETE COSINE TRANSFORM). The discrete cosine transform is a fast transform. It is a widely used and robust method for image compression. It has excellent compaction for highly correlated data. DCT has fixed basis images DCT gives good compromise between information packing ability and computational complexity. JPEG 2000 image compression standard makes use of DWT (DISCRETE WAVELET TRANSFORM). DWT can be used to reduce the image size without losing much of the resolutions computed and values less than a pre-specified threshold are discarded. Thus it reduces the amount of memory required to represent given image. The literature survey in the chronological order is as follows: According to Y. Tim Tsai, (1) in 1991-color image compression for Single-Chip Cameras Single-chip cameras could be incorporated a CFA (color filter array) on the sensor to obtain color information. Color interpolation could then needed to recover the color images. Color-coding was conventionally implemented after the inter- polation process. Two drawbacks inherited are a long processing time, and a requirement for a large memory buffer. Direct coding of the sensor data before color interpolation results in enormous artifacts and poor compression efficiency. Four new ideas for compressing color images obtained from single-chip CFA imagers have been presented. Be- cause of the special characteristics of the input, perceptually weighted coefficient quantization should be modified or removed. The color data should be separated in 3 colors. The best method was selected by comparing the compression efficiency and final image quality. The suggested method has the advantage of low processing time and low bit rate. Takio Kurita (2) in 1993 proposed a Method of Block Truncation Coding for Color Image Compression. A BTC algorithm for color image compression and its mod- ification were presented. The algorithms require a significantly small computational load and little memory and preserve sharp edges as well as the ordinary monochrome BTC. Further improvements of performance of bit rate reduction will be achieved by using the same techniques pro- posed for the monochrome BTC. The quality of reconstructed images also will be improved by adaptively combining a spatial coding technique and the color BTC method like the hybrid image compression method for medical images. Gaurav Sharma (3) in 1997 proposed a Digital Color Imaging, procedure that provide, research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented using vector-space notation and terminology. Present- day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication surveyed, and a forecast of research trends are attempted.