THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

In this article, we have reviewed the reasons why we (collectively) want to love or leave the venerable (but perhaps hoary) MSE. We have also reviewed emerging alternative signal fidelity measures and discussed their potential application to a wide variety of problems. The message we are trying to send here is not that one should abandon use of the MSE nor to blindly switch to any other particular signal fidelity measure. Rather, we hope to make the point that there are powerful, easy-to-use, and easy-to-understand alternatives that might be deployed depending on the application environment and needs. While we expect (and indeed, hope) that the MSE will continue to be widely used as a signal fidelity measure, it is our greater desire to see more advanced signal fidelity measures being used, especially in applications where perceptual criteria might be relevant. Ideally, the performance of a new signal processing algorithm might be compared to other algorithms using several fidelity criteria. Lastly, we hope that we have given further motivation to the community to consider recent advanced signal fidelity measures as design criteria for optimizing signal processing algorithms and systems. It is in this direction that we believe that the greatest benefit eventually lies.

Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures

A morphable model for the synthesis of 3D faces

The development of the Internet in recent years has made it possible and useful to access many different information systems anywhere in the world to obtain information. While there is much research on the integration of heterogeneous information systems, most commercial systems stop short of the actual integration of available data. Data fusion is the process of fusing multiple records representing the same real-world object into a single, consistent, and clean representation.This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data fusion, namely, uncertain and conflicting data values. We give an overview and classification of different ways of fusing data and present several techniques based on standard and advanced operators of the relational algebra and SQL. Finally, the article features a comprehensive survey of data integration systems from academia and industry, showing if and how data fusion is performed in each.

Data fusion

A fast and effective image fusion method is proposed for creating a highly informative fused image through merging multiple images. The proposed method is based on a two-scale decomposition of an image into a base layer containing large scale variations in intensity, and a detail layer capturing small scale details. A novel guided filtering-based weighted average technique is proposed to make full use of spatial consistency for fusion of the base and detail layers. Experimental results demonstrate that the proposed method can obtain state-of-the-art performance for fusion of multispectral, multifocus, multimodal, and multiexposure images.

/pdf/image-fusion-with-guided-filtering-4bhdh8vaii.pdf

Image Fusion With Guided Filtering

We present a variational model to perform the fusion of an arbitrary number of images while preserving the salient information and enhancing the contrast for visualization. We propose to use the structure tensor to simultaneously describe the geometry of all the inputs. The basic idea is that the fused image should have a structure tensor which approximates the structure tensor obtained from the multiple inputs. At the same time, the fused image should appear `natural' and `sharp' to a human interpreter. We therefore propose to combine the geometry merging of the inputs with perceptual enhancement and intensity correction. This is performed through a minimization functional approach which implicitly takes into account a set of human vision characteristics.

http://wims.math.ecnu.edu.cn/ChunLi/Seminar_20111011/Used%20papers_FanFaming/%5b%5dvariational_Image_Fusion_for_Enhanced_Visualization_A_Variational_Approach.pdf

Image Fusion for Enhanced Visualization: A Variational Approach

We propose a framework for constructing adaptive wavelet decompositions using the lifting scheme. A major requirement is that perfect reconstruction is possible without any overhead cost. We restrict ourselves to the update lifting stage. It is assumed that the update filter utilizes local gradient information to adapt itself to the signal in the sense that smaller gradients "evoke" stronger update filters. As a result, sharp transitions in a signal will not be smoothed to the same extent as regions that are more homogeneous. The approach taken in this paper differs from other adaptive schemes found in the literature in the sense that no bookkeeping is required in order to have perfect reconstruction.

/pdf/adaptive-lifting-schemes-with-perfect-reconstruction-68ideba2b0.pdf

Adaptive lifting schemes with perfect reconstruction

We propose a multiresolution fusion algorithm which combines aspects of region and pixel-based fusion. We use multiresolution decompositions to represent the input images at different scales, and introduce a multiresolution/multimodal segmentation to partition the image domain at these scales. The basic idea is to use this segmentation to guide the fusion process. A region-based multiresolution approach allows us to consider low-level as well as intermediate-level structures, and to impose data-dependent consistency constraints based on spatial, inter and intra-scale dependencies.

A region-based multiresolution image fusion algorithm

Towards content-oriented patent document processing

Background:Current diagnosis of heart failure with preserved ejection fraction (HFpEF) is suboptimal. We tested the hypothesis that comprehensive machine learning (ML) of left ventricular function ...

https://hal.archives-ouvertes.fr/hal-02282401/document

Gemma Piella

Papers

Image Fusion for Enhanced Visualization: A Variational Approach

Adaptive lifting schemes with perfect reconstruction

A region-based multiresolution image fusion algorithm

Towards content-oriented patent document processing

Machine learning analysis of left ventricular function to characterize heart failure with preserved ejection fraction