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# Note for Digital Image Processing - DIP By JNTU Heroes

• Digital Image Processing - DIP
• Note
• Jawaharlal Nehru Technological University Anantapur (JNTU) College of Engineering (CEP), Pulivendula, Pulivendula, Andhra Pradesh, India - JNTUACEP
• Computer Science Engineering
• 2 Topics
• 23327 Views
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#### Note for Digital Image Processing - DIP By JNTU Heroes

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► What is Digital Image Processing? Digital Image Image is a representation, likeness, or imitation of an object or thing Common Digital image formats include: Binary images or single bit images, Gray scale images, Color images A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels. Pixel values typically represent gray levels, colours, heights, opacities etc. Pixels are the elements of a digital image — a two-dimensional function f (x,y), The amplitude of f is called intensity or x and y are spatial coordinates. gray level at the point (x, y) What is meant by Digital Image Processing? Explain how digital images can be represented? An image may be defined as a two-dimensional function, f(x, y), where x and y are spatial (plane) coordinates, and the amplitude OR intensity OR gray level of f at any pair of coordinates (x, y) . When x, y, and the amplitude values of f are all finite, discrete quantities, we call the image a digital image. each of these has a particular location and value. These elements are referred to as picture elements, image elements, pels, and pixels. Pixel is the term most widely used to denote the elements of a digital imag. The field of digital image processing refers to processing digital images by means of a digital computer.   A color image is just three functions pasted together. We can write this as a “vector-valued” function: r ( x, y) f ( x, y) g( x, y)

b( x, y)

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Representing Digital Images: Continuous image, say a film positive is a function of 2 continuous variables f (s,t) This can be converted into a digital image by scanning; sampling and quantization Sample into a 2D array f(x,y), M rows and N columns, (x,y) = discrete coordinates, x = 0, 1, 2,…, M-1 and y = 0, 1, 2…, N-1 Section of the real plane spanned by the coordinates of an image = spatial domain x and y are called spatial variables or spatial coordinates f (x,y) can be represented in three ways: Image plotted as a surface, Image displayed as a visual intensity array, Numerical array

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Dynamic range = ratio of maximum measurable intensity to minimum detectable intensity level in the system Rule: upper limit determined by saturation, lower limit determined by noise Contrast = difference in intensity between the highest and the lowest intensity levels in an image High dynamic range => high contrast expected Low dynamic range => dull, washed-out gray Look Coordinate convention used to represent digital images ► The representation of an M×N numerical array as a 0,0 a a A M 1,1 ... 1,1 ... a ... a 1,0 M 1,0 a a 0, N 1 ... ... a 1, N 1 ... ... 0,1 a M 1, N 1 ► The representation of an M×N numerical array f (x, y) f (1,1) f (1,2) ... f (1, N) f (2,1) f (2,2) ... f (2, N) ... f (M,1) ... ... ... f (M,2) ... f (M, N) f (x, y) f (0,0) f (0,1) ... f (0, N 1) f (1,0) f (1,1) ... f (1, N 1) ... f (M 1,0) ... ... ... f (M 1,1) ... f (M 1, N 1)