AI Article Synopsis
- The method estimates defocus maps from a single natural image by analyzing how defocusing impacts spectrum amplitude at object edges.
- It first determines the blur amount at edge locations, then uses this information to create a complete defocus map across the image through a specialized optimization process.
- The approach accounts for both light refraction effects and the image’s blur texture, showing improved reliability in defocus map estimation compared to existing techniques.
Article Abstract
We present an effective method for defocus map estimation from a single natural image. It is inspired by the observation that defocusing can significantly affect the spectrum amplitude at the object edge locations in an image. By establishing the relationship between the amount of spatially varying defocus blur and spectrum contrast at edge locations, we first estimate the blur amount at these edge locations, then a full defocus map can be obtained by propagating the blur amount at edge locations over the entire image with a nonhomogeneous optimization procedure. The proposed method takes into consideration not only the affect of light refraction but also the blur texture of an image. Experimental results demonstrate that our proposed method is more reliable in defocus map estimation compared to various state-of-the-art methods.
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| http://dx.doi.org/10.1364/OL.38.001706 | DOI Listing |
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