Lossy trapdoor functions (Peikert and Waters, STOC ’08) are an intriguing and powerful cryptographic primitive. Their main applications are simple and black-box constructions of chosen-ciphertext secure encryption, as well as collision-resistant hash functions and oblivious transfer. An appealing property of lossy trapdoor functions is the ability to realize them from a variety of number-theore...

Bloom ltering is an important technique for space e cient storage of a conservative approximation of a set S. The set stored may have up to some speci ed number of false positive members, but all elements of S are included. In this paper we consider lossy dictionaries that are also allowed to have false negatives , i.e., leave out elements of S. The aim is to maximize the weight of included key...

This paper investigates a measurement method that characterizes lossy printed multiconductor transmission lines, its accuracy, the choice of measurement representations, and some simple approximations. We illustrate the method with measurements of a pair of lossy coupled asymmetric microstrip lines.

This article presents a polynomial-based image compression scheme, which consists of using the color model (YUV) to represent contents and two-dimensional polynomial coding (first-order) with variable block size according correlation between neighbor pixels. The residual part for all bands is analyzed into two parts, most important (big) part, least (small) parts. Due significant subjective imp...

Lossy trapdoor functions (LTFs) were first introduced by Peikert and Waters (STOC’08). Since their introduction, lossy trapdoor functions have found numerous applications. They can be used as tools to construct important cryptographic primitives such as injective one-way trapdoor functions, chosen-ciphertext-secure public key encryptions, deterministic encryptions, et al. In this paper, we focu...

Developers can use lossy compression on images and many other artifacts to reduce size and improve network transfer times. Native program instructions, however, are typically not considered candidates for lossy compression since arbitrary losses in instructions may dramatically affect program output. In this paper we show that lossy compression of compiled native instructions is possible in cer...

An integer reversible implementation of multiple component transform is significant for lossless, unified lossy/lossless and progressive lossy-lossless multi-component or hyper-spectral image coding. In this proposal, we present a reversible integer mapping method for invertible linear transforms. Its effectiveness was evaluated using 2 6-band Landsat TM images and an 80-component hyper-spectra...

This paper develops a theoretical framework for lossy source coding that treats it as a statistical problem, in analogy to the approach to universal lossless coding suggested by Rissanen’s Minimum Description Length (MDL) principle. Two methods for selecting efficient compression algorithms are proposed, based on lossy variants of the Maximum Likelihood and MDL principles. Their theoretical per...

Non-destructive testing and reconstruction of lossy non-uniform transmission lines require solving inverse scattering problems for inhomogeneous one-dimensional (1D) lossy media. Often the source waveform used to probe the medium is unknown, since it cannot be measured separately. This paper shows that the blind deconvolution problem of reconstructing both an unknown source and an unknown lossy...

: Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes impercep...