Multiresolution pyramid techniques can improve the efficiency of basic vision algorithms by orders of magnitude. They will be key to developing practical vision systems to perform challenging tasks in real time. However, these efficiencies cannot be fully realized when pyramid-based algorithms are implemented on machines with conventional SIMD mesh and pipeline architectures. We describe a segm...

We describe a statistical model for images decomposed in an overcomplete wavelet pyramid. Each neighborhood of pyramid coefficients is modeled as the product of a Gaussian vector of known covariance, and an independent hidden positive scalar random variable. We propose an efficient Bayesian estimator for the pyramid coefficients of an image degraded by linear distortion (e.g., blur) and additiv...

This paper presents a new method for image compression by neural networks. First, we show that we can use neural networks in a pyramidal framework, yielding the so-called PCA pyramids. Then we present an image compression method based on the PCA pyramid, which is similar to the Laplace pyramid and wavelet transform. Some experimental results with real images are reported. Finally, we present a ...

We construct a formal power series on several variables that encodes many statistics on non-decreasing Dyck paths. In particular, we use this formal power series to count peaks, pyramid weights, and indexed sums of pyramid weights for all nondecreasing Dyck paths of length 2n. We also show that an indexed sum on pyramid weights depends only on the size and maximum element of the indexing set.

Modern processors, e.g., Intel SGX, allow applications to isolate secret code and data in encrypted memory regions called enclaves. While encryption effectively hides the contents of memory, the sequence of address references issued by the secret code leaks information. This is a serious problem because these leaks can easily break the confidentiality guarantees of enclaves. In this paper, we e...