We have witnessed great interest and a wealth of promise in content-based image retrieval as an emerging technology. While the last decade laid foundation to such promise, it also paved the way for a large number of new techniques and systems, got many new people involved, and triggered stronger association of weakly related fields. In this article, we survey almost 300 key theoretical and empirical contributions in the current decade related to image retrieval and automatic image annotation, and in the process discuss the spawning of related subfields. We also discuss significant challenges involved in the adaptation of existing image retrieval techniques to build systems that can be useful in the real world. In retrospect of what has been achieved so far, we also conjecture what the future may hold for image retrieval research.

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Image retrieval: Ideas, influences, and trends of the new age

The PASCAL Visual Object Classes Challenge

A survey of content-based image retrieval with high-level semantics

Exploring and identifying structure is even more important for multivariate data than univariate data, given the difficulties in graphically presenting multivariate data and the comparative lack of parametric models to represent it. Unfortunately, such exploration is also inherently more difficult.

Multivariate Density Estimation

▶ Addresses the accessibility, usability, and, ultimately, acceptability of Information Society Technologies by anyone, anywhere, at anytime, and through any media and device. ▶ Focuses on theoretical, methodological, and empirical research, of both technological and non-technological nature. ▶ Features papers that report on theories, methods, tools, empirical results, reviews, case studies, and best-practice examples.

Universal access in the information society

In this paper an efficient filtering technique intended for the reduction of mixed Gaussian and impulsive noise in digital color images is presented. The proposed method is utilizing the concept of trimmed cumulative distances assigned to pixels from the local filtering window, which serve as measures of a local image homogeneity. The filter output is defined as a weighted average of the pixels in the processing window and the weights are constructed using the measures of pixel corruption. The proposed design is very fast and outperforms the state-of-the-art denoising schemes in terms of image restoration quality measures.

http://ieeexplore.ieee.org/iel7/6746871/6757586/06757815.pdf

Fast technique for mixed Gaussian and impulsive noise suppression in color images

Shift-and-add is an approach employed to mitigate the phenomenon of resolution degradation in images acquired through a turbulent medium. Using this technique, a large number of consecutive short exposures is registered below the coherence time of the atmosphere or other blurring medium. The acquired images are shifted to the position of the brightest speckle and stacked together to obtain high resolution and high signal-to-noise frame. In this Letter, we present a highly efficient method for determination of frame shifts, even if in a single frame the object cannot be distinguished from the background noise. The technique utilizes our custom genetic algorithm, which iteratively evolves a set of image shifts. We used the maximal energy of stacked images as an objective function for shifts estimation and validate the efficiency of the method on simulated and real images of simple and complex sources. Obtained results confirmed that our proposed method allows for the recovery of spatial distribution of objects even only 2% brighter than their background. The presented approach extends significantly current limits of image reconstruction with the use of shift-and-add method. The applications of our algorithm include both the optical and the infrared imaging. Our method may be also employed as a digital image stabilizer in extremely low light level conditions in professional and consumer applications.

Beyond the current noise limit in imaging through turbulent medium.

A novel approach to the problem of edge preserving smoothing, which allows an image to be broken into a set of homogeneous regions, is proposed and evaluated. The new algorithm is based on combined forward and backward anisotropic diffusion with an incorporated time dependent cooling process. This method is able to remove image noise efficiently while preserving and enhancing image edges.

Forward and backward anisotropic diffusion filtering for color image enhancement

The main problem addressed in this paper is as follows: a system applying the proposed framework should retrieve all images whose color structure is similar to that of the given query image, independently on the applied lossy coding. We propose an approach based on the color histogram approximation using the Gaussian Mixture Model. The proposed method incorporates the information on the spatial distribution of the color image pixels utilizing the bilateral filtering scheme. The retrieval results were evaluated on large databases of natural color images and the usefulness of the proposed technique was compared with some commonly known retrieval methods operating on color histograms.

/pdf/effective-color-image-retrieval-based-on-the-gaussian-2gnmacp78r.pdf

Effective color image retrieval based on the gaussian mixture model

The single cell gel electrophoresis, called Comet Assay, is a microelectrophoretic technique of direct visualization of the DNA damage at the cell level. In the comet assay, the cells suspended in an agarose gel on a microscope slide are subjected to lysis, unwinding of DNA and electrophoresis. Under the influence of weak, static electric field, charged DNA migrates away from the nucleus, forming the so called comet. The damage is quantified by measuring the amount of the genetic material, which migrates from the nucleus to form the comet tail. In this paper we present three novel methods of the comet tail and head extraction, which allow to quantify the cell’s damage.

Bogdan Smolka

Papers

Fast technique for mixed Gaussian and impulsive noise suppression in color images

Beyond the current noise limit in imaging through turbulent medium.

Forward and backward anisotropic diffusion filtering for color image enhancement

Effective color image retrieval based on the gaussian mixture model

Segmentation of the Comet Assay Images