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0116136 Computer Vision

0116136 Computer Vision. Introduction to Digital Images. Digital Images. Digital Image : • in general, image is a function of four variables • For color image, λ takes three different values corresponding to red, green and blue components,

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0116136 Computer Vision

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  1. 0116136Computer Vision IntroductiontoDigitalImages

  2. Digital Images Digital Image: • in general, image is a function of four variables • For color image, λ takes three different values corresponding to red, green and blue components, • For constant λ (black and white), the image function becomes where t is a time variable for a sequence of frames. • For a constant t, f becomes which is a function of two spatial variables.

  3. Grayscale Image Sensing Systems:

  4. ColorImageImageSensingSystems:

  5. CCD cameras are much more sensitive than the eye

  6. Sampling (Resolution)

  7. Grayscale Quantization Level:

  8. Color Image Quantization Level

  9. Image Enhancement

  10. Digital Image • These values are called “gray levels ”. They are real, non-negative. • Image is of finite size : They are zero outside a finite region, since an optical system has a bounded field of view. • Whenever necessary, we will assume that image functions are analytically well -behaved, e.g. integrable, invertible FT. • After sampling, we have a discrete set of real numbers. (m,n) • After quantization, the resulting quantized gray levels can be regarded as integers f(m,n) • Thus after sampling and quantization, we can assume that a digital image is a rectangular array rectangular array of integer values. • Pixel : An element of a digital image is called a “picture element”. • Binary Image : If there are just two values, e.g. black and white, we usually represent them by 0 and 1.

  11. Except on borders of the array, any point (m,n) has 8 neighbor pixels • Note that diagonal neighbors units away from (m,n) while horizontal and vertical neighbors are only 1 unit away.

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