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Showing 1 to 7 of 7 for “"blurred image"”.

  1. Motion blur removal from photographs

    … To remove blur, we need to (i) estimate how the image is blurred (i.e. the blur kernel or the point-spread function) and (ii) restore a natural looking image through deconvolution. Blur kernel estimation is challenging because the algorithm needs to distinguish the correct imageblur pair from …

    mit Repository record for Motion blur removal from photographs (opens in a new tab)

  2. Inverse filtering by signal reconstruction from phase

    A common problem that arises in image processing is that of performing inverse filtering on an image that has been blurred. Methods for doing this have been developed, but require fairly accurate knowledge of the magnitude of the Fourier transform of the blurring function and are sensitive to noise …

    mit Repository record for Inverse filtering by signal reconstruction from phase (opens in a new tab)

  3. Adaptation to Interocular Differences in Blur

    Adaptation to a blurred image causes a physically focused image to appear too sharp, and shifts the point of subjective focus toward the adapting blur, consistent with a renormalization of perceived focus. We examined whether and how this adaptation normalizes to differences in blur between the two …

    unr Repository record for Adaptation to Interocular Differences in Blur (opens in a new tab)

  4. Ανάπτυξη συστήματος τομογραφικής απεικόνισης σε εξομοιωτή ακτινοθεραπείας

    … involve a number of projections of the acquired image matrices as well as parallel translations and summing. Application of this method has resulted in an estimated 60-fold reduction of computing time, thus maintaining computer power requirements to a minimum. A technique has also been developed …

    greece Repository record for Ανάπτυξη συστήματος τομογραφικής απεικόνισης σε εξομοιωτή ακτινοθεραπείας (opens in a new tab)

  5. Deconvolution and sparsity based image restoration

    … sparse representation are the two key areas in image and signal processing. In this thesis the classical image restoration problem is addressed using these two modalities. Image restoration, such as deblurring, dnoising, and in-painting belongs to the class of ill-posed linear inverse problems, …

    aus-cath Repository record for Deconvolution and sparsity based image restoration (opens in a new tab)

  6. Deconvolution and sparsity based image restoration

    … sparse representation are the two key areas in image and signal processing. In this thesis the classical image restoration problem is addressed using these two modalities. Image restoration, such as deblurring, dnoising, and in-painting belongs to the class of ill-posed linear inverse problems, …

    anu Repository record for Deconvolution and sparsity based image restoration (opens in a new tab)