IEEE TRANSACTIONS ON IMAGE PROCESSING
IEEE TRANSACTIONS ON IMAGE PROCESSING(英文缩写 IEEE T IMAGE PROCESS),ISSN 1057-7149,eISSN 1941-0042 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
指标来源：jcr_cas_ifqb
期刊简介
暂无简介。
历年影响因子趋势
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IEEE TRANSACTIONS ON IMAGE PROCESSING 最新收录文献
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New spatial measure for dispersed-dot halftoning assuring good point distribution in any density.
As a core component of dispersed-dot halftoning, this paper focuses on the definition of new measures for giving or measuring good point distributions in a plane. By defining good point distributions …
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Color filter array demosaicking using high-order interpolation techniques with a weighted median filter for sharp color edge preservation.
Demosaicking is an estimation process to determine missing color values when a single-sensor digital camera is used for color image capture. In this paper, we propose a number of new methods based on …
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Noniterative MAP reconstruction using sparse matrix representations.
We present a method for noniterative maximum a posteriori (MAP) tomographic reconstruction which is based on the use of sparse matrix representations. Our approach is to precompute and store the inver…
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A total variation-based algorithm for pixel-level image fusion.
In this paper, a total variation (TV) based approach is proposed for pixel-level fusion to fuse images acquired using multiple sensors. In this approach, fusion is posed as an inverse problem and a lo…
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Attraction-repulsion expectation-maximization algorithm for image reconstruction and sensor field estimation.
In this paper, we propose an attraction-repulsion expectation-maximization (AREM) algorithm for image reconstruction and sensor field estimation. We rely on a new method for density estimation to addr…
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n-SIFT: n-dimensional scale invariant feature transform.
We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's pe…
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Intelligent acquisition and learning of fluorescence microscope data models.
We propose a mathematical framework and algorithms both to build accurate models of fluorescence microscope time series, as well as to design intelligent acquisition systems based on these models. Mod…
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Accurate image rotation using hermite expansions.
In this paper, we propose an approach for the accurate rotation of a digital image using Hermite expansions. This exploits the fact that if a 2-D continuous bandlimited Hermite expansion is rotated, t…
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Hierarchical Bayesian sparse image reconstruction with application to MRFM.
This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hie…
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Super-resolution without explicit subpixel motion estimation.
The need for precise (subpixel accuracy) motion estimates in conventional super-resolution has limited its applicability to only video sequences with relatively simple motions such as global translati…