A 5x5 image f(x, y) with a grayscale level of 2-bit and a 3x3 convolution mask h(x, y) are given below. (a) [2 marks] Indicate the pixel values of output image g(x, y) obtained by: g(x, y) =f(x, y)*h(x, y). Suppose that a zero padding is added for the pixels at the perimeters of f(x, y) in 2-D discrete convolution. (b) [1 mark] Describe the mathematical meanings of this mask h(x, y). ) [1 mark] Give an image processing application using this mask, and explain the output image g(x, y). (d) [2 marks] Calculate the entropy of the image f(x, y). (e) [1 mark] What is the possible highest lossless compression ratio for f(x, y)? = 1 1 1 1 1 -1 -1 -1 2 2 2 2 2 * 0 0 0 3 3 3 3 3 1 1 1 2 2 2 2 2 1 1 1 1 1 f(x, y) h(x, y) y g(x, y) A 5x5 image f(x, y) with a grayscale level of 2-bit and a 3x3 convolution mask h(x, y) are given below. (a) [2 marks] Indicate the pixel values of output image g(x, y) obtained by: g(x, y) =f(x, y)*h(x, y). Suppose that a zero padding is added for the pixels at the perimeters of f(x, y) in 2-D discrete convolution. (b) [1 mark] Describe the mathematical meanings of this mask h(x, y). ) [1 mark] Give an image processing application using this mask, and explain the output image g(x, y). (d) [2 marks] Calculate the entropy of the image f(x, y). (e) [1 mark] What is the possible highest lossless compression ratio for f(x, y)? = 1 1 1 1 1 -1 -1 -1 2 2 2 2 2 * 0 0 0 3 3 3 3 3 1 1 1 2 2 2 2 2 1 1 1 1 1 f(x, y) h(x, y) y g(x, y)