Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Fast interscale wavelet denoising of Poisson-corrupted images
Signal Processing
IEEE Transactions on Image Processing
Multiscale modeling and estimation of Poisson processes with application to photon-limited imaging
IEEE Transactions on Information Theory
A statistical multiscale framework for Poisson inverse problems
IEEE Transactions on Information Theory
Wavelet-domain filtering for photon imaging systems
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Sparse geometric image representations with bandelets
IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
Wavelets, Ridgelets, and Curvelets for Poisson Noise Removal
IEEE Transactions on Image Processing
Image Denoising in Mixed Poisson–Gaussian Noise
IEEE Transactions on Image Processing
Hi-index | 0.08 |
Platelet is a multiscale representation developed for Poisson noise-removal from images. The existing platelet denoising algorithm requires O(N^4) computations for an NxN image. In this paper, we introduce geometric platelet algorithm, which has a reduced computational complexity of O(N^3logN). In the platelet algorithm, the exhaustive search required to compute an optimal platelet representation of the image is the major contributing factor to its computational requirements. In the proposed algorithm, this step is made faster by first learning the local geometry of the image by using Lucas-Kanade gradient descent algorithm. This geometric information is used to reduce the number of required searches, thereby reducing the run-time of the algorithm. We further extend the geometric platelet algorithm to include quadlet atoms, constructed from second-order bivariate polynomials. We validate the performance of the proposed algorithms by applying them on the simulated as well as real-world Poisson noisy images.