scholarly journals Variation diminishing-type properties for multivariate sampling Kantorovich operators

2020 ◽  
Vol 13 (4) ◽  
pp. 595-605
Author(s):  
Laura Angeloni ◽  
Danilo Costarelli ◽  
Marco Seracini ◽  
Gianluca Vinti ◽  
Luca Zampogni
Keyword(s):  
Compact Support ◽  
Digital Images ◽  
Type Estimate ◽  
Step Functions ◽  
Variation Diminishing ◽  
Kantorovich Operators

Abstract In this paper we establish a variation-diminishing type estimate for the multivariate Kantorovich sampling operators with respect to the concept of multidimensional variation introduced by Tonelli. A sharper estimate can be achieved when step functions with compact support (digital images) are considered. Several examples of kernels have been presented.

Approximation by max-product sampling Kantorovich operators with generalized kernels

2019 ◽  
pp. 1-26 ◽  
Author(s):  
Lucian Coroianu ◽  
Danilo Costarelli ◽  
Sorin G. Gal ◽  
Gianluca Vinti
Keyword(s):  
Uniform Convergence ◽  
Real Axis ◽  
Modulus Of Continuity ◽  
Higher Dimensions ◽  
Jackson Type ◽  
Convergence Properties ◽  
Type Estimate ◽  
Quantitative Estimates ◽  
Uniform Modulus Of Continuity ◽  
Kantorovich Operators

In a recent paper, for max-product sampling operators based on general kernels with bounded generalized absolute moments, we have obtained several pointwise and uniform convergence properties on bounded intervals or on the whole real axis, including a Jackson-type estimate in terms of the first uniform modulus of continuity. In this paper, first, we prove that for the Kantorovich variants of these max-product sampling operators, under the same assumptions on the kernels, these convergence properties remain valid. Here, we also establish the [Formula: see text] convergence, and quantitative estimates with respect to the [Formula: see text] norm, [Formula: see text]-functionals and [Formula: see text]-modulus of continuity as well. The results are tested on several examples of kernels and possible extensions to higher dimensions are suggested.

scholarly journals New integral type operators

Filomat ◽  
2017 ◽  
Vol 31 (9) ◽  
pp. 2851-2865
Author(s):  
Emre Deniz ◽  
Ali Aral ◽  
Gulsum Ulusoy
Keyword(s):  
Pointwise Convergence ◽  
Weighted Space ◽  
Approximation Theorem ◽  
Modulus Of Smoothness ◽  
Integral Type ◽  
Type Estimate ◽  
Lp Space ◽  
Weighted Modulus ◽  
Direct Approximation ◽  
Kantorovich Operators

In this paper we construct new integral type operators including heritable properties of Baskakov Durrmeyer and Baskakov Kantorovich operators. Results concerning convergence of these operators in weighted space and the hypergeometric form of the operators are shown. Voronovskaya type estimate of the pointwise convergence along with its quantitative version based on the weighted modulus of smoothness are given. Moreover, we give a direct approximation theorem for the operators in suitable weighted Lp space on [0,?).

Reduction in size of digital images: does it lead to less detectability or loss of diagnostic information?

1998 ◽  
Vol 27 (2) ◽  
pp. 93-96 ◽  
Author(s):  
C H Versteeg ◽  
G C H Sanderink ◽  
S R Lobach ◽  
P F van der Stelt
Keyword(s):  
Digital Images ◽  
Diagnostic Information

Development of a system for craniofacial analysis from monitor-displayed digital images

1999 ◽  
Vol 28 (2) ◽  
pp. 123-126 ◽  
Author(s):  
E Gotfredsen ◽  
J Kragskov ◽  
A Wenzel
Keyword(s):  
Digital Images

Authentication of Digital Image using Exif Metadata and Decoding Properties

2018 ◽  
pp. 335-341 ◽  
Author(s):  
D. P. Gangwar ◽  
Anju Pathania
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Software Tools ◽  
Robust Analysis

This work presents a robust analysis of digital images to detect the modifications/ morphing/ editing signs by using the image’s exif metadata, thumbnail, camera traces, image markers, Huffman codec and Markers, Compression signatures etc. properties. The details of the whole methodology and findings are described in the present work. The main advantage of the methodology is that the whole analysis has been done by using software/tools which are easily available in open sources.

Selection of the efficient video data processing strategy based on the analysis of statistical digital images characteristics

2018 ◽  
Vol 91 (3) ◽  
pp. 107-114
Author(s):  
Mykhailo Palamar ◽  
Myroslava Yavorska ◽  
Mykhailo Strembitskyi ◽  
Volodymyr Strembitskyi
Keyword(s):  
Data Processing ◽  
Digital Images ◽  
Video Data ◽  
Processing Strategy ◽  
Efficient Video ◽  
Selection Of

I Think We’re Alone Now

2020 ◽  
Vol 6 (4) ◽  
pp. 183-210
Author(s):  
Erin Nunoda
Keyword(s):  
Public Sphere ◽  
Digital Images ◽  
Empty Space ◽  
The Public ◽  
Youtube Videos ◽  
The Public Sphere

This article examines YouTube videos (primarily distributed by a user named Cecil Robert) that document so-called dead malls: unpopulated, unproductive, but not necessarily demolished consumerist sites that have proliferated in the wake of the 2008 recession. These works link digital images of mall interiors with pop-song remixes so as to re-create the experience of hearing a track while standing within the empty space; manipulating the songs’ audio frequencies heightens echo effects and fosters an impression of ghostly dislocation. This article argues that these videos locate a potentiality in abandoned mall spaces for the exploration of queer (non)relations. It suggests that the videos’ emphasis on lonely, unconsummated intimacies questions circuitous visions of the public sphere, participatory dynamics online, and the presumably conservative biopolitics (both at its height and in its memorialization) of mall architecture.

A METHOD FOR AUTOMATIC BLIND ESTIMATION OF ADDITIVE NOISE VARIANCE IN DIGITAL IMAGES

2010 ◽  
Vol 69 (19) ◽  
pp. 1681-1702
Author(s):  
V. V. Lukin ◽  
S. K. Abramov ◽  
A. V. Popov ◽  
P. Ye. Eltsov ◽  
Benoit Vozel ◽  
...  
Keyword(s):  
Additive Noise ◽  
Digital Images ◽  
Blind Estimation ◽  
Noise Variance

CONTRAST ENHANCEMENT IN GRAYSCALE DIGITAL IMAGES APPLYING ATOMIC FUNCTIONS IN FUZZY LOGIC

2013 ◽  
Vol 72 (19) ◽  
pp. 1787-1801
Author(s):  
C. M. Vargas-Martinez ◽  
Victor Filippovich Kravchenko ◽  
Vladimir Il'ich Ponomarev ◽  
Juan Carlos Sanchez-Garcia
Keyword(s):  
Fuzzy Logic ◽  
Contrast Enhancement ◽  
Digital Images
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