RE 17.3 This image demonstrates the effects of quantization error. The upper left image is a coronary artery image 8 bits(256 levels or shades of gray) per pixel. The upper right image has 4 bits/pixel (16 levels). The lower left image bits/pixel(8 levels). The lower right image has 2 bits/pixel (4 levels). Note the false contouring in the images as the number of possible levels in the pixel representation is reduced. This false contouring is the quantization error, and as the number of levels increases the quantization error decreases because fewer mistakes are being made in the representation of false contouring in the picture. One usually needs at least 6 bits or 64 gray levels to represent an image adequately. Higher-quality imaging systems use 8 bits(256 levels)or even as many as 10 bits(1024 levels)per ixel. In most applications, the human observer cannot distinguish quantization error when there are more than 256 levels. (Many times the number of gray levels is cited in bytes. One byte is 8 bits, i.e., high-quality monochrome digital imaging systems use one byte per pixel) One of the problems briefly mentioned previously is the large number of pixels needed to represent an i. y which translates into a large amount of digital data needed for the representation. A 512 X 512 image wit 8 bits/pixel(1 byte/pixel)of gray level representation requires 2,097, 152 bits of computer data to describe it.A typical computer file that contains 1000 words usually requires only about 56,000 bits to describe it. The 512 X 512 image is 37 times larger! (A picture is truly worth more than 1000 words. )This data requirement is one of the major problems with digital imaging, given that the storage of digital images in a computer file system is expensive. Perhaps another example will demonstrate this problem. Many computers and word processing systems have the capability of transmitting information over telephone lines to other systems at data rates of 2400 bits per second. At this speed it would require nearly 15 minutes to transmit a 512 X 512 image! Moving objects are imaged digitally by taking digital snapshots of them, i. e, digital video. True digital imaging would acquire about 30 images/s to capture all the important motion in a scene. At 30 images/s, with each image sampled at 512 X 512 and with 8 bits/pixel, the system must handle 62, 914, 560 bits/s. Only very expensive acquisition systems are capable of handling these large data rates The grea do on a computer can be done to a digital image. Recall that a digital image is Just a(huge)matrix test advantage of digital images is that they can be processed on a computer. Any type of operation that one car of numbers. Digital image processing is the process of using a computer to extract useful information from this matrix. Processing that cannot be done optically or with analog systems(such as early video systems)can be easily done on computers. The disadvantage is that a large amount of data needs to be processed and on ome small computer systems this can take a long time(hours). we shall examine image processing in more detail in the next subsection and discuss some of the computer hardware issues in a later chapt c2000 by CRC Press LLC© 2000 by CRC Press LLC of false contouring in the picture. One usually needs at least 6 bits or 64 gray levels to represent an image adequately. Higher-quality imaging systems use 8 bits (256 levels) or even as many as 10 bits (1024 levels) per pixel. In most applications, the human observer cannot distinguish quantization error when there are more than 256 levels. (Many times the number of gray levels is cited in bytes. One byte is 8 bits, i.e., high-quality monochrome digital imaging systems use one byte per pixel.) One of the problems briefly mentioned previously is the large number of pixels needed to represent an image, which translates into a large amount of digital data needed for the representation. A 512 3 512 image with 8 bits/pixel (1 byte/pixel) of gray level representation requires 2,097,152 bits of computer data to describe it. A typical computer file that contains 1000 words usually requires only about 56,000 bits to describe it. The 512 3 512 image is 37 times larger! (A picture is truly worth more than 1000 words.) This data requirement is one of the major problems with digital imaging, given that the storage of digital images in a computer file system is expensive. Perhaps another example will demonstrate this problem. Many computers and word processing systems have the capability of transmitting information over telephone lines to other systems at data rates of 2400 bits per second. At this speed it would require nearly 15 minutes to transmit a 512 3 512 image! Moving objects are imaged digitally by taking digital snapshots of them, i.e., digital video. True digital imaging would acquire about 30 images/s to capture all the important motion in a scene. At 30 images/s, with each image sampled at 512 3 512 and with 8 bits/pixel, the system must handle 62,914,560 bits/s. Only very expensive acquisition systems are capable of handling these large data rates. The greatest advantage of digital images is that they can be processed on a computer. Any type of operation that one can do on a computer can be done to a digital image. Recall that a digital image is just a (huge) matrix of numbers. Digital image processing is the process of using a computer to extract useful information from this matrix. Processing that cannot be done optically or with analog systems (such as early video systems) can be easily done on computers. The disadvantage is that a large amount of data needs to be processed and on some small computer systems this can take a long time (hours). We shall examine image processing in more detail in the next subsection and discuss some of the computer hardware issues in a later chapter. FIGURE 17.3 This image demonstrates the effects of quantization error. The upper left image is a coronary artery image with 8 bits (256 levels or shades of gray) per pixel. The upper right image has 4 bits/pixel (16 levels). The lower left image has 3 bits/pixel (8 levels). The lower right image has 2 bits/pixel (4 levels). Note the false contouring in the images as the number of possible levels in the pixel representation is reduced. This false contouring is the quantization error, and as the number of levels increases the quantization error decreases because fewer mistakes are being made in the representation