Image Processing Homeworks

HW1

• Affine Transformation
• Nearest & Bilinear 코드 구현

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HW2

1. Gamma Transformation

• Input image & Gamma = 0.6 & Gamma = 0.4 & Gamma = 0.3
  

2. Histogram Equalization

• Input image & Histogram
  

• Output image & Histogram
  

3. Spatial Domain Filtering

• Box kernel 11x11 - Zero Padding & Mirror Padding
  

• Box kernel 25x25 - Zero Padding & Mirror Padding
  

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HW3

1. Frequency domain Filtering

• Low pass Gaussian kernel Fourier spectrum & phase angle (H(u,v))
  

• Input image Fourier spectrum & phase angle (F(u,v))
  

• G(u,v)의 Fourier spectrum
  

• Input & Output
  

2. Combination of the spectrum and phase angle to image formation - 2-D DFT and IDFT

• input img_1 & input img_2
  

• img_1의 Fourier spectrum & phase angle
  

• img_2의 Fourier spectrum & phase angle
  

• img_1의 Fourier spectrum과 img_2의 phase angle을 사용하여 Reconstuct한 Image
  

• img_2의 Fourier spectrum과 img_1의 phase angle을 사용하여 Reconstuct한 Image
  

3. Notch Filter

• Input Image

• Input Image의 Fourier spectrum

• Fourier transform multiplied by a Butterworth notch reject filter transfer function

• Output Image

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HW4

Image Restoration

1. Spatial Non-linear Filtering

• Salt & Pepper Noise 생성

  • Salt noise (ps = 0.1)
    

  • Pepper noise (pp = 0.1)
    

  • Salt & Pepper noise (ps = pp = 0.05)
    

• Image degraded by Salt & Pepper noise (pp = 0.1 , ps = 0.1 , pp = ps = 0.1)
  

• Contraharmonic Mean Filter

  • Q = 1.5
    

  • Q = 0
    

  • Q = -1.5
    

• Median Filter
  

• Adaptive Median Filter
  

2. Frequency Domain Filtering

• Original Image
  

• Add Atmospheric Turbulence
  

• Wiener Filter
  

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HW5

Color Image Processing

1. Convert RGB to HSI / Convert HSI to RGB
2. Sobel Filtering

• RGB color space
  
• HSI color space