There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

The 11th edition of Harrison's Principles of Internal Medicine welcomes Anthony Fauci to its editorial staff, in addition to more than 85 new contributors. While the organization of the book is similar to previous editions, major emphasis has been placed on disorders that affect multiple organ systems. Important advances in genetics, immunology, and oncology are emphasized. Many chapters of the book have been rewritten and describe major advances in internal medicine. Subjects that received only a paragraph or two of attention in previous editions are now covered in entire chapters. Among the chapters that have been extensively revised are the chapters on infections in the compromised host, on skin rashes in infections, on many of the viral infections, including cytomegalovirus and Epstein-Barr virus, on sexually transmitted diseases, on diabetes mellitus, on disorders of bone and mineral metabolism, and on lymphadenopathy and splenomegaly. The major revisions in these chapters and many

Harrison's Principles of Internal Medicine

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

When is nearest neighbor meaningful

Unsharp masking is an effective enhancement tool to improve the visual quality of fine details in images. However, it also amplifies noisy and over-enhances steep edges. To address this problem, this paper proposes a parametric rational unsharp masking. It utilizes the horizontal and vertical gain factors to enhance image details in two directions independently. Experiments and comparisons are provided to demonstrate its excellent enhancement performance.

Parametric rational unsharp masking for image enhancement

Image fusion is the effective combination of multiple images into a single fused image. The goal of the fusion is use the
similar and complementary information of the source images in order to obtain an informative depiction of the scene for
further processing. Many multi-scale image fusion algorithms have been formulated on the basis that the human visual
system is sensitive to edge information. However, these algorithms make use of standard mathematical operators, which
do not reflect human visual system characteristics over a large range of background luminance intensities. Accordingly,
this paper proposes new image fusion algorithms using a new Parameterized Logarithmic Stationary Wavelet Transform
(PL-SWT), which combines the advantages of the Stationary Wavelet Transform (SWT) and the Parameterized
Logarithmic Image Processing (PLIP) model, a parameterized framework for processing images. An analysis of the
PLIP model shows that it is capable of providing a balance between logarithmic and standard mathematical operators
based on image dependent characteristics. Consequently, the use of the parameterized model is extended for to both
pixel- and region-based fusion approaches. Experimental results via computer simulation illustrate the improved
performance of the proposed image fusion algorithms by both qualitative and quantitative means.

Pixel- and region-based image fusion using the parameterized logarithmic stationary wavelet transform

The problem of color image composition from original grayscale images is considered. A few models are proposed and analyzed, which are based on the observation done on many color images that in average a proportion exists between primary colors in images. Re-coloring of grayscale images are performed in the RGB color model and the Golden, Silver, Aesthetic ratios and other rules of proportions are considered between the primary colors. The gray is used as the main color to be map into the three colors at each pixel. We also describe a parameterized model with the given ratio of re-coloring images.

Re-coloring of grayscale images: models with aesthetic and golden proportions

Image alignment and mosaicing are usually performed on a set of overlapping images, using features in the area of
overlap for seamless stitching. In many cases such images have different size and shape. So we need to crop panoramas
or to use image extrapolation for them. This paper focuses on novel image inpainting method based on modified
exemplar-based technique. The basic idea is to find an example (patch) from an image using local binary patterns, and
replacing non-existed (‘lost’) data with it. We propose to use multiple criteria for a patch similarity search since often in
practice existed exemplar-based methods produce unsatisfactory results. The criteria for searching the best matching uses
several terms, including Euclidean metric for pixel brightness and Chi-squared histogram matching distance for local
binary patterns. A combined use of textural geometric characteristics together with color information allows to get more
informative description of the patches. In particular, we show how to apply this strategy for image extrapolation for
photo stitching. Several examples considered in this paper show the effectiveness of the proposed approach on several
test images.

Image extrapolation for photo stitching using nonlocal patch-based inpainting

This paper offers a review of effective methods of image representation, or visibility images in enhancement applied to the thermal images and night vision images. The quality of images is estimated by quantitative enhancement measures, which are based on the Weber-Fechner, Michelson, and other parameterized ratio and entropy-type measures. We also apply the concept of visibility images, by using different types of gradient operators which allow for extracting and enhancing features in images. Examples of gradient visibility images, Weber-Fechner, and Michelson contrast, log and power Michelson and Weber visibility images are given. Experimental results show the effectiveness of visibility images in enhancing thermal and night vision images. Different methods of image enhancement in spatial and frequency domains are analyzed on the thermal and night vision images, by using the visibility images. Experimental results show that visibility images can be used in processing in spatial and frequency domains. Here, we mention the alpha-rooting by the classical discrete Fourier transform (DFT) and quaternion DFT, the retinex method, and new gradient based histogram equalization.

Sos S. Agaian

Papers

Parametric rational unsharp masking for image enhancement

Pixel- and region-based image fusion using the parameterized logarithmic stationary wavelet transform

Re-coloring of grayscale images: models with aesthetic and golden proportions

Image extrapolation for photo stitching using nonlocal patch-based inpainting

Thermal and night vision image visibility and enhancement