- C.-T. Shen, W.-L. Hwang, and S.-C. Pei, “Spatially-Varying Out-Of-Focus Image Deblurring with L1-2 Optimization and a Guided Blur Map", in Proc. of 37th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 1069-1072, 2012.
- System:
- L1-2 Deblurring:
- Results #1 (Blurry Input, Ours, Blur Map): The data is downloaded from Zhuo et al’s webpage. Please notice the regions within different depth.
- Results #2 (Blurry Input, Ours, Blur Map): The data is downloaded from Zhuo et al’s webpage. We remove the out-of-focus while extend the depth-of-field.
- Results #3 (Blurry Input, Ours, Blur Map): The data is captured using Camera Control Pro 2 with a tripod. Since two men stand at the different depth, the input image suffers spatially-varying out-of-focus blur. As we can see, we reconstruct the blurry faces.
- Results #4 (Blurry Input, Ours, Blur Map): The data is captured using Camera Control Pro 2 with a tripod and focus on the ball.
Since two men stand at the different depth, the input image suffers spatially-varying out-of-focus blur. As we can see, we reconstruct the blurry faces while keep the ball latent. - Results #5 (Blurry Input, Ours, Blur Map) : The data is captured using a camera phone, and it is out-of-focus. We remove the blur while enhance the chinese characters and texture parts.
- Results #6 (Blurry Input, Ours, Blur Map) : The data is captured using a camera phone, and it is out-of-focus. We remove the blur while enhance the lady’s face and texture parts. The lady is a Traditional Chinese Doctor. She is observing the patient’s movement.
- Results #7 (Blurry Input, Ours, Blur Map): The data is captured using a digital still camera(DSC), and it is out-of-focus. We remove the blur in the background while enhance the lady’s face and texture parts.
- Results #8 (Blurry Input, Ours, Blur Map): The data is part of the image captured using a DSLR, and it is out-of-focus. We remove the blur in the background while keep the hair latent.
- Results #9 (Blurry Input, Ours, Blur Map): The data is downloaded from Xu et al.’s webpage. Although the data suffers from motion-blur, our method still gives a certain result and extends the depth of field. Since our method is not for depth estimation, we set the smooth regions as in-focus regions so as to suppress the ringing artifacts.
- Results #10 (Blurry Input, Ours, Blur Map): The data is downloaded from Xu et al.’s webpage. Although the data suffers from motion-blur, our method still gives a certain result and extends the depth of field.
- Results #11 (Blurry Input, Ours, Blur Map): The data is downloaded from Xu et al.’s webpage. Although the data suffers from motion-blur, our method still gives a certain result and extends the depth of field. Since our method is not for depth estimation, we set the smooth regions as in-focus regions so as to suppress the ringing artifacts.
- Results #12 (Blurry Input, Ours, Blur Map): The data is downloaded from Xu et al.’s webpage. Although the data suffers from motion-blur, our method still gives a certain result and extends the depth of field.
Spatially-Varying Out-Of-Focus Image Deblurring with L1-2 Optimization and a Guided Blur Map, ICASSP2012.
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