A comparison of coloured image compression methods / Norshita Mat Nayan

The idea of image compression is not new. There has always been an interest in economical and efficient communication. Image compression is a method of eliminating redundancies should be built in normal language representation. 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. A few techniques or methods can be used to compress an image. Segmentation Based Coding, Directional Filtering Based Coding, Recognition Based Coding, Fractal, Wavelet and JPEG are famous techniques in image compression. This research explores three comparative methods, which are widely used. They are Wavelet Method, Fractal Method and JPEG Method. The main objective of this research is to find the best method for colour image compression between Wavelet, Fractal and JPEG using three parameters which are compressed file size, compression ratio and peak signal noise ratio. Image compression system has been developed using C++ Builder and 200 data from the Internet was using with different file sizes (range between 359 Kb to 725 Kb) were used for system testing purposes. Are four phases involved in this research are data collection, designing, development and testing and evaluation phase. On finding shows that Wavelet method is the best method for colour image compression compared to Fractal and JPEG.