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

Color image segmentation: advances and prospects

One of the challenging issues for Orthogonal Frequency Division Multiplexing (OFDM) system is its high Peak-to-Average Power Ratio (PAPR). In this paper, we review and analysis different OFDM PAPR reduction techniques, based on computational complexity, bandwidth expansion, spectral spillage and performance. We also discuss some methods of PAPR reduction for multiuser OFDM broadband communication systems.

https://engold.ui.ac.ir/~sabahi/Advanced%20digital%20communication/An%20Overview%20Peak-to-Average%20Power%20Ratio%20Reduction%20Reduction%20Techniques%20for%20OFDM%20Signals.pdf

An Overview: Peak-to-Average Power Ratio Reduction Techniques for OFDM Signals

Computer and Robot Vision Vol. 1, by R.M. Haralick and Linda G. Shapiro, Addison-Wesley, 1992, ISBN 0-201-10887-1.

Computer and Robot Vision

This paper presents a new reflectance model for rendering computer synthesized images. The model accounts for the relative brightness of different materials and light sources in the same scene. It describes the directional distribution of the reflected light and a color shift that occurs as the reflectance changes with incidence angle. The paper presents a method for obtaining the spectral energy distribution of the light reflected from an object made of a specific real material and discusses a procedure for accurately reproducing the color associated with the spectral energy distribution. The model is applied to the simulation of a metal and a plastic.

A reflectance model for computer graphics

This paper proposes a tone-reproduction method that uses a neural network and modified sigmoid function to perceptually compensate the characteristics of an output device. An inkjet printer was used as the output device the characteristics of which were analyzed by colorimetric measurement. The measured device-characteristic data for primary inks were then used to model the I/O characteristics of the device and a modified sigmoid function was exploited as the optimal tone-reproduction curve for the printer. In the actual application of the printing process, the mapping function between the proposed tone-curve and the input signal of the device was constructed as an LUT and then used as a preprocessor. As a result, the proposed algorithm produced a detailed color reproduction in the mid-tone range and enhanced the image contrast in the shadow-tone regions.

Colorimetric Printer Calibration using Modified Sigmoidal Tone-Curve Function

The characterization process for the accurate color reproduction in mobile phone with camera and LCD is popular. The camera and LCD characterization, gamut mapping process is necessary to map the camera's input color stimulus, CIEXYZ value, into the LCD's output color stimulus. Each characterization is the process estimating the relation between input and output signals. In case of LCD, because of output device, the output color stimulus for the arbitrary input signal can be measured by spectro-radiometer However, in the camera, as the input device, the characterization is an inaccurate and needs the manual works in the process obtaining the output signal because the input signal can not be generated. Moreover, after gamut mapping process, the noise is increased because the optimized gamma tone curve of camera for the noise is distorted by the characterization. Thus, this paper proposed the system of obtaining the output signal of camera and the method of gamma correction for the noise. The camera's output signal is obtained by RGB values of patches from captured the color chart image. However, besides the illumination, the error for the location of the chart in the viewfinder is generated when many camera modules are captured the chart. The method of correcting the position to correct the error from manual works. The position of camera is estimated by captured image. This process and moving of camera is accomplished repeatedly, and the optimized position can be obtained. Moreover, the lightness curve of camera output is corrected partly to reduce the noise from the characterization process.

https://www.koreascience.kr:443/article/JAKO200814357777495.pdf

Improved characterization method for mobile phone camera and LCD display

Illuminant chromaticity estimation via optimization of RGB channel standard deviation

Most display characterization methods, such as the gain- offset-gamma model and S-curve model, generally assume that dis- plays have two fundamental characteristics, channel-chromaticity constancy and channel independence. Consequently, based on the assumption of channel-chromaticity constancy, only one electro- optical transfer function (EOTF) is used for each channel to estab- lish the relation between the digital input values and the output lu- minance levels. Meanwhile, based on the channel-independence assumption, the channel color values are simply summed to acquire mixed color values. However, these assumptions are not so appli- cable in the case of liquid crystal-based mobile displays. Accord- ingly, modifications are required to enable the application of conven- tional display characterization methods to mobile displays. Therefore, this study proposes the modeling of distinct EOTFs in terms of the X, Y, and Z values for each channel to consider the differences among the EOTFs resulting from channel-chromaticity inconstancy. In addition, to overcome the poor additivity property among the channels due to channel interaction, the proposed method also models and uses the EOTFs of the X, Y, and Z values for the interchannel components cyan, magenta, yellow, and gray. Experimental results confirm that the mobile display color values predicted by the proposed characterization method are more accu- rate than those predicted by other characterization methods due to considering the channel-chromaticity inconstancy and/or channel dependence of the display. © 2006 Society for Imaging Science and Technology. DOI: 10.2352/J.ImagingSci.Technol.200650:4349

Characterization of Error Reduction in Mobile Liquid Crystal Display Using Distinct XYZ Electro-Optical Transfer Functions for Each Channel and Interchannel Components

Yeong-Ho Ha

Papers

Colorimetric Printer Calibration using Modified Sigmoidal Tone-Curve Function

Improved characterization method for mobile phone camera and LCD display

Illuminant chromaticity estimation via optimization of RGB channel standard deviation

Characterization of Error Reduction in Mobile Liquid Crystal Display Using Distinct XYZ Electro-Optical Transfer Functions for Each Channel and Interchannel Components

Pseudo-Linearly Modified IHS Color Model and its Application to Color Image Enhancement.