The document discusses different methods for denoising images in the spatial and frequency domains. It introduces spatial domain denoising techniques like mean filtering, median filtering, and adaptive filtering. It then explains how spatial domain images can be transformed into the frequency domain using Fourier and wavelet transforms. This allows denoising based on frequency content, where high frequencies associated with noise can be removed. It concludes by mentioning the CVPR Denoising Workshop as a resource.

2. Denoising in spatial domain
• mean filter
• Median filter
• Max filter/Min filter
• Alpha-trimmed mean filter
• Adaptive filter
• Notch filter

3. Denoising with spatial domain
Mean filter
Median filter
https://preventionyun.tistory.com/33

4. Mean filter & Median filter

5. Denoising with Spatial domain? Frequency domain?

6. Denoising with Spatial domain? Frequency domain?
Fourier
transform
Inverse Fourier
transform

7. Base of Fourier transform
base : (1,0), (0,1) ➔ sin, cos
frequency

8. Fourier transform
Spatial domain frequency domain

9. 2D Spatial domain & frequency domain
# of Pixels (# of sampling) ➔ determine ‘highest frequency’
Window size (width) ➔ determine ‘frequency resolution’

10. Sampling and Frequency
impossible
possible
2s
→ 최대 1/2s frequency

11. Window width and freqeuncy

12. Spatial domain to Frequency domain
Low freq high freq

13. Frequency domain denoising

14. Wavelet transform
Frequency만 조절 Frequency + scale 조절

15. Wavelet transform
sacle 조절 = window width 조절
Scale 증가
Scale 증가
Scale 증가

16. Discrete Wavelet transform

17. Stationary Wavelet transform

18. CVPR Denoising Workshop

19. CVPR Denoising Workshop

20. Thank You