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, 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.

Grayscale Image Sensing Systems:

Color Image Image Sensing Systems:

CCD cameras are much more sensitive than the eye

Sampling (Resolution)

Grayscale Quantization Level:

Color Image Quantization Level

Image Enhancement

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.

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.