Blind restoration of atmospherically degraded images by automatic - - PowerPoint PPT Presentation

blind restoration of atmospherically degraded images by
SMART_READER_LITE
LIVE PREVIEW

Blind restoration of atmospherically degraded images by automatic - - PowerPoint PPT Presentation

Blind restoration of atmospherically degraded images by automatic best step-edge detection Ormi Shacham, Oren Haik, Yitzhak Yitzhaky Ben-Gurion University, Department of Electro-Optics Engineering, Israel Pattern Recognition Letters, Volume 28


slide-1
SLIDE 1

Reporter : Chih-Chieh Lien <cclien@islab.csie.thu.edu.tw> Reporter : Chih-Chieh Lien <cclien@islab.csie.thu.edu.tw>

Blind restoration of atmospherically degraded images by automatic best step-edge detection

Ormi Shacham, Oren Haik, Yitzhak Yitzhaky Ben-Gurion University, Department of Electro-Optics Engineering, Israel Pattern Recognition Letters, Volume 28 , Issue 15 (November 2007) Page 2094-2103

slide-2
SLIDE 2

Outline

 Blind restoration  Atmospherically degraded image  Proposed method  Experimental Result  Conclusion

slide-3
SLIDE 3

Blind restoration

 Only available data is the recorded image

itself.

 An image restoration process in this case is

called blind restoration.

slide-4
SLIDE 4

Atmospherically degraded images

 In horizontal long-distance imaging  Degraded due to atmospheric effects

slide-5
SLIDE 5

Proposed method

Degraded image Edge detection Atmospheric MTF Calculated Wiener filter Restored image

slide-6
SLIDE 6

Edge detection

 Canny edge detection used to produce

single-line edge, Provides non-broken edges

 Evaluation of edge length and straightness  Small-scale evaluation  Large-scale evaluation

slide-7
SLIDE 7

Small-scale evaluation

 Weighting code given by relationship with

neighbors.

 Have one or zero neighbor: 1  Has neighbors angels of 45,90,135,180 will

be assigned 2,3,4, and 5

slide-8
SLIDE 8

Small-scale evaluation

slide-9
SLIDE 9

Small-scale evaluation

 Provide information for Large-scale

evaluation: Locate longer straight edges

slide-10
SLIDE 10

Edge detection: Result

slide-11
SLIDE 11

Contract and homogeneity of edge sides

 Examine which edges has high contrast

and homogeneous regions from both sides (step-edge)

 Done by taking a square region

surrounding the center pixel of the edge and observing the histogram of the pixels in that area.

slide-12
SLIDE 12

Contract and homogeneity of edge sides

slide-13
SLIDE 13

Contract and homogeneity of edge sides

 Small size of the square region will have a

better chance to be the image of a close to an ideal step-edge.

 But it should be large enough to include the

whole significant part of the atmospheric blur.

slide-14
SLIDE 14

Calculation of the atmospheric MTF and image restoration

 Using the step-edge obtained to calculate

MTF (Modulation Transfer Function) H(u,v).

 Extracted MTF is used for restoring the

atmospherically degraded image.

slide-15
SLIDE 15

Result: synthetically blurred image

slide-16
SLIDE 16

Result: synthetically blurred image

slide-17
SLIDE 17

Result: real degraded image

slide-18
SLIDE 18

Conclusion

 The method in the paper seems works well

in real degraded images.

 A good edge detection is very important for

image restoration.

slide-19
SLIDE 19

END