In this chapter, the authors have briefed about images, digital images, how the digital images can be processed. Image types like binary image, grayscale image, color image, and indexed image and various image formats are explained. It highlights the various fields where digital image processing can be used. This chapter introduces a variety of concepts related to digital image formation in a human eye. The mechanism of the human visual system is discussed. The authors illustrate the steps of image processing. Explanation on different elements of digital image processing systems like image acquisition, and others are also provided. The components required for capturing and processing the image are discussed. Concepts of image sampling, quantization, image representation are discussed. It portrays the operations of the image during sampling and quantization and the two operations of sampling which is oversampling and under-sampling. Readers can appreciate the key difference between oversampling and under-sampling applied to digital images.
Top2. Digital Image Processing
Any three-dimensional scene represented in the form of a two-dimension is said to be an image this image can be represented in the form of f (x, y) where x, y are spatial coordinates and f is the intensity at that point. Images are of two types: analog image and digital image. The analog image has a continuous range of values representing position and intensity. For example, an image produced on the screen of a CRT monitor is an analog image. The storage requirement for such images is very high. In digital image x, y and f are all finite, and discrete quantities. Hence, the conversion of an analog image to a digital image is very necessary before processing it. This conversion is just done using two simple steps- sampling and quantization. In sampling, it discretizes in the coordinate values x, and y whereas in quantization, it discretizes in the amplitude value f. Each element in a digital image is said to be a pixel or pels or picture element or image elements. Manipulation of this digital image using a digital computer is said to be a digital image processing.(Shilpa Hiremath et al., 2018).
Digital image processing has many advantages when compared to analog image processing below mentioned are a few of them,
Three major use of digital image processing are:
Example: filtering of the noise present in an image, enhancing the content of an image like contrast enhancement, deblurring, and also remote sensing.
Example: Industry machine vision for product assembly and inspection, detect and track the target automatically, fingerprint and face recognition, machine processing of aerial and satellite imagery for weather prediction or crop assessment.
· Efficient storage and transmission: An image is processed to reduce the space required to store that image and if it's transmitted it should consume less bandwidth. An image usually contains two entities namely: information & redundancy. In image processing to achieve better storage or transmission of an image, image compression is applied where the redundancy part is removed and only the information content is present (Gonzalez, R. C., Woods, R. E., & Eddins, S. L.,2004).
Example: image compression