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Holographic representations of images

IEEE Transactions on Image Processing, 1998
We discuss a new type of holographic image representations that have advantages in a "distributed" world. We call these representations holographic. Arbitrary portions of a holographic representation enable reconstruction of the whole image, with distortions that decrease gradually with the increase in the size of the portions available.
Alfred M. Bruckstein   +2 more
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A representation for mammographic image processing

Medical Image Analysis, 1995
Mammographic image analysis is typically performed using standard, general-purpose algorithms. We note the dangers of this approach and show that an alternative physics-model-based approach can be developed to calibrate the mammographic imaging process. This enables us to obtain, at each pixel, a quantitative measure of the breast tissue.
Ralph Highnam   +2 more
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Multiple representations and sparse representation for image classification

Pattern Recognition Letters, 2015
To extract salient features from images is significant for image classification. Deformable objects suffer from the problem that a number of pixels may have varying intensities. In other words, pixels at the same positions of training samples and test samples of an object usually have different intensities, which makes it difficult to obtain salient ...
Yong Xu 0001   +2 more
openaire   +1 more source

Images of Representation

Issues in Legal Scholarship, 2005
This paper is one of a series of papers commemorating Richard Stewart’s important article, The Reformation of American Administrative Law. Among other things, Stewart’s 1975 article identified “interest representation†as the central idea that animated a series of important and disparate developments in administrative law doctrine.
openaire   +1 more source

A-Optimal Projection for Image Representation

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016
We consider the problem of image representation from the perspective of statistical design. Recent studies have shown that images are possibly sampled from a low dimensional manifold despite of the fact that the ambient space is usually very high dimensional. Learning low dimensional image representations is crucial for many image processing tasks such
Xiaofei He 0001   +3 more
openaire   +3 more sources

Invariant representation in image processing

Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2002
The paper discusses the role of invariance in image processing, specifically the desire to discriminate against unwanted variations in the scene while maintaining the power to tell the difference between object-intrinsic characteristics and scene-accidental conditions. It provides an analysis and references of what are directly observables in a general
Smeulders, A.W.M.   +2 more
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Discriminative Image Representation for Classification

2014
The Bag-of-visual Words (BoW) image representation is a classical method applied for various problems in the fields of multimedia and computer vision. During the process of BoW image representation, one of the core problems is to generate discriminative and descriptive visual words.
Zhize Wu   +3 more
openaire   +1 more source

A Survey of Orthogonal Moments for Image Representation: Theory, Implementation, and Evaluation

ACM Computing Surveys, 2023
Shuren Qi, Yushu Zhang, Jiantao Zhou
exaly  

Quantum image representation: a review

Quantum Machine Intelligence, 2022
Marina O. Lisnichenko   +1 more
openaire   +1 more source

Image Representation

2021
Chiwoo Park, Yu Ding
openaire   +1 more source

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