Compression and Encoding of Image: Image Formats

Abstract

Digital image is a discrete 2D signal having information of intensity in terms of primary colors (either red, green, blue (RGB), or cyan, magenta, yellow, black (CMYK)) for each separation of each pixel. Just by considering a small RGB image of size 10?×?10, we can measure the size of the image data as 3?×?8?×?10?×?10?=?2400 bits, where intensity of each color separation or each pixel is 1 byte or 8 bits. Hence, we can understand, it requires huge data to represent a sufficiently large image. In today’s world of image transmission through network, fast representation on webpage, and storing image information, the size of data plays a resistive role. Therefore, it is very important to employ image compression suitably. The term “suitable” is added intentionally to address the quality issue of image against the trade-off with compression ratio. It is well understood that there is a merely inverse relationship between the factors “quality” and “compression ratio”. The quality is a direct illustration of information in the image. As the amount of detailing in the image is varied, the difficulty in choice between quality and compression ratio is also varied. This chapter is especially important for any kind of application development in image processing. The lossless and lossy compression methodology with trade-off has been described in the first half of this chapter. Second half of the chapter describes the process and algorithm of encoding the raw and compressed image formats. We have presented one C++ code for reading 24-bit BMP image. The code is available in the supplementary electronic material (CD) also. The two popular compressed image formats, JPEG and GIF are also discussed and the required code snippets are presented.